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- checkpoints/unimedclip/unimed_clip_vit_b16.pt +3 -0
 - checkpoints/unimedclip/unimed_clip_vit_l14_large_text_encoder.pt +3 -0
 - exp-rank-16/resnet/fewshot_100_percent/checkpoints/best_model/checkpoint.pth +3 -0
 - exp-rank-16/resnet/fewshot_100_percent/checkpoints/best_model/lora_weights.safetensors +3 -0
 - exp-rank-16/resnet/fewshot_100_percent/checkpoints/best_model/model.pth +3 -0
 - exp-rank-16/resnet/fewshot_100_percent/checkpoints/checkpoint_last/checkpoint.pth +3 -0
 - exp-rank-16/resnet/fewshot_100_percent/checkpoints/checkpoint_last/lora_weights.safetensors +3 -0
 - exp-rank-16/resnet/fewshot_100_percent/checkpoints/checkpoint_last/model.pth +3 -0
 - exp-rank-16/resnet/fewshot_100_percent/training_20250402-140103.log +147 -0
 - exp-rank-16/resnet/fewshot_100_percent/training_20250402-140719.log +396 -0
 - exp-rank-16/resnet/fewshot_10_percent/checkpoints/best_model/checkpoint.pth +3 -0
 - exp-rank-16/resnet/fewshot_10_percent/checkpoints/best_model/lora_weights.safetensors +3 -0
 - exp-rank-16/resnet/fewshot_10_percent/checkpoints/best_model/model.pth +3 -0
 - exp-rank-16/resnet/fewshot_10_percent/checkpoints/checkpoint_last/checkpoint.pth +3 -0
 - exp-rank-16/resnet/fewshot_10_percent/checkpoints/checkpoint_last/lora_weights.safetensors +3 -0
 - exp-rank-16/resnet/fewshot_10_percent/checkpoints/checkpoint_last/model.pth +3 -0
 - exp-rank-16/resnet/fewshot_10_percent/training_20250403-005625.log +164 -0
 - exp-rank-16/resnet/fewshot_30_percent/checkpoints/best_model/checkpoint.pth +3 -0
 - exp-rank-16/resnet/fewshot_30_percent/checkpoints/best_model/lora_weights.safetensors +3 -0
 - exp-rank-16/resnet/fewshot_30_percent/checkpoints/best_model/model.pth +3 -0
 - exp-rank-16/resnet/fewshot_30_percent/checkpoints/checkpoint_last/checkpoint.pth +3 -0
 - exp-rank-16/resnet/fewshot_30_percent/checkpoints/checkpoint_last/lora_weights.safetensors +3 -0
 - exp-rank-16/resnet/fewshot_30_percent/checkpoints/checkpoint_last/model.pth +3 -0
 - exp-rank-16/resnet/fewshot_30_percent/training_20250403-011001.log +208 -0
 - exp-rank-16/resnet/fewshot_75_percent/checkpoints/best_model/checkpoint.pth +3 -0
 - exp-rank-16/resnet/fewshot_75_percent/checkpoints/best_model/lora_weights.safetensors +3 -0
 - exp-rank-16/resnet/fewshot_75_percent/checkpoints/best_model/model.pth +3 -0
 - exp-rank-16/resnet/fewshot_75_percent/checkpoints/checkpoint_last/checkpoint.pth +3 -0
 - exp-rank-16/resnet/fewshot_75_percent/checkpoints/checkpoint_last/lora_weights.safetensors +3 -0
 - exp-rank-16/resnet/fewshot_75_percent/checkpoints/checkpoint_last/model.pth +3 -0
 - exp-rank-16/resnet/fewshot_75_percent/training_20250403-013013.log +332 -0
 - exp-rank-16/vit/fewshot_100_percent/checkpoints/best_model/checkpoint.pth +3 -0
 - exp-rank-16/vit/fewshot_100_percent/checkpoints/best_model/lora_weights.safetensors +3 -0
 - exp-rank-16/vit/fewshot_100_percent/checkpoints/best_model/model.pth +3 -0
 - exp-rank-16/vit/fewshot_100_percent/checkpoints/checkpoint_last/checkpoint.pth +3 -0
 - exp-rank-16/vit/fewshot_100_percent/checkpoints/checkpoint_last/lora_weights.safetensors +3 -0
 - exp-rank-16/vit/fewshot_100_percent/checkpoints/checkpoint_last/model.pth +3 -0
 - exp-rank-16/vit/fewshot_100_percent/training_20250403-031835.log +398 -0
 - exp-rank-16/vit/fewshot_10_percent/checkpoints/best_model/checkpoint.pth +3 -0
 - exp-rank-16/vit/fewshot_10_percent/checkpoints/best_model/lora_weights.safetensors +3 -0
 - exp-rank-16/vit/fewshot_10_percent/checkpoints/best_model/model.pth +3 -0
 - exp-rank-16/vit/fewshot_10_percent/checkpoints/checkpoint_last/checkpoint.pth +3 -0
 - exp-rank-16/vit/fewshot_10_percent/checkpoints/checkpoint_last/lora_weights.safetensors +3 -0
 - exp-rank-16/vit/fewshot_10_percent/checkpoints/checkpoint_last/model.pth +3 -0
 - exp-rank-16/vit/fewshot_10_percent/training_20250403-005422.log +168 -0
 - exp-rank-16/vit/fewshot_30_percent/checkpoints/best_model/checkpoint.pth +3 -0
 - exp-rank-16/vit/fewshot_30_percent/checkpoints/best_model/lora_weights.safetensors +3 -0
 - exp-rank-16/vit/fewshot_30_percent/checkpoints/best_model/model.pth +3 -0
 - exp-rank-16/vit/fewshot_30_percent/checkpoints/checkpoint_last/checkpoint.pth +3 -0
 - exp-rank-16/vit/fewshot_30_percent/checkpoints/checkpoint_last/lora_weights.safetensors +3 -0
 
    	
        checkpoints/unimedclip/unimed_clip_vit_b16.pt
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| 1 | 
         
            +
            2025-04-02 14:01:03,540 - INFO - Arguments: Namespace(datasets=['aml', 'fundus', 'mammo_calc', 'mammo_mass', 'pneumonia', 'oct', 'pbc', 'bloodmnist', 'breastmnist', 'octmnist', 'pneumoniamnist', 'retinamnist'], use_corruptions=False, severity_range=[1, 3], corruption_types=None, fewshot=None, epochs=20, batch_size=256, lr=0.0001, weight_decay=0.0001, temperature=2.0, alpha=0.5, backbone='resnet', lora_rank=16, lora_alpha=16, lora_dropout=0.1, device=device(type='cuda', index=6), gpu=6, seed=42, num_workers=4, output_dir='./outputs/exp2/resnet/fewshot_100_percent', log_interval=10, save_interval=1, eval_interval=1, resume=None)
         
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            2025-04-02 14:01:03,540 - INFO - Creating dataloaders for datasets: ['aml', 'fundus', 'mammo_calc', 'mammo_mass', 'pneumonia', 'oct', 'pbc', 'bloodmnist', 'breastmnist', 'octmnist', 'pneumoniamnist', 'retinamnist']
         
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            2025-04-02 14:02:54,817 - INFO - Initializing RobustMedClip model
         
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            2025-04-02 14:03:03,707 - INFO - Starting training
         
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            2025-04-02 14:03:03,714 - INFO - Epoch 1/20
         
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            2025-04-02 14:03:07,364 - ERROR - Error in batch 0: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
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            2025-04-02 14:03:14,883 - ERROR - Error in batch 42: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 49 | 
         
            +
            2025-04-02 14:03:14,983 - ERROR - Error in batch 43: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 50 | 
         
            +
            2025-04-02 14:03:15,074 - ERROR - Error in batch 44: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 51 | 
         
            +
            2025-04-02 14:03:15,567 - ERROR - Error in batch 45: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 52 | 
         
            +
            2025-04-02 14:03:15,720 - ERROR - Error in batch 46: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 53 | 
         
            +
            2025-04-02 14:03:15,825 - ERROR - Error in batch 47: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 54 | 
         
            +
            2025-04-02 14:03:15,912 - ERROR - Error in batch 48: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 55 | 
         
            +
            2025-04-02 14:03:16,195 - ERROR - Error in batch 49: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 56 | 
         
            +
            2025-04-02 14:03:16,575 - ERROR - Error in batch 50: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 57 | 
         
            +
            2025-04-02 14:03:16,658 - ERROR - Error in batch 51: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 58 | 
         
            +
            2025-04-02 14:03:16,751 - ERROR - Error in batch 52: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 59 | 
         
            +
            2025-04-02 14:03:16,965 - ERROR - Error in batch 53: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 60 | 
         
            +
            2025-04-02 14:03:17,505 - ERROR - Error in batch 54: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 61 | 
         
            +
            2025-04-02 14:03:17,575 - ERROR - Error in batch 55: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 62 | 
         
            +
            2025-04-02 14:03:17,649 - ERROR - Error in batch 56: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 63 | 
         
            +
            2025-04-02 14:03:17,775 - ERROR - Error in batch 57: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 64 | 
         
            +
            2025-04-02 14:03:18,444 - ERROR - Error in batch 58: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 65 | 
         
            +
            2025-04-02 14:03:18,555 - ERROR - Error in batch 59: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 66 | 
         
            +
            2025-04-02 14:03:18,657 - ERROR - Error in batch 60: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 67 | 
         
            +
            2025-04-02 14:03:18,755 - ERROR - Error in batch 61: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 68 | 
         
            +
            2025-04-02 14:03:19,198 - ERROR - Error in batch 62: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 69 | 
         
            +
            2025-04-02 14:03:19,280 - ERROR - Error in batch 63: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 70 | 
         
            +
            2025-04-02 14:03:19,370 - ERROR - Error in batch 64: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 71 | 
         
            +
            2025-04-02 14:03:19,460 - ERROR - Error in batch 65: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 72 | 
         
            +
            2025-04-02 14:03:19,962 - ERROR - Error in batch 66: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 73 | 
         
            +
            2025-04-02 14:03:20,041 - ERROR - Error in batch 67: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 74 | 
         
            +
            2025-04-02 14:03:20,127 - ERROR - Error in batch 68: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 75 | 
         
            +
            2025-04-02 14:03:20,224 - ERROR - Error in batch 69: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 76 | 
         
            +
            2025-04-02 14:03:20,877 - ERROR - Error in batch 70: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 77 | 
         
            +
            2025-04-02 14:03:20,980 - ERROR - Error in batch 71: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 78 | 
         
            +
            2025-04-02 14:03:21,066 - ERROR - Error in batch 72: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 79 | 
         
            +
            2025-04-02 14:03:21,148 - ERROR - Error in batch 73: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 80 | 
         
            +
            2025-04-02 14:03:21,735 - ERROR - Error in batch 74: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 81 | 
         
            +
            2025-04-02 14:03:21,843 - ERROR - Error in batch 75: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 82 | 
         
            +
            2025-04-02 14:03:21,944 - ERROR - Error in batch 76: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 83 | 
         
            +
            2025-04-02 14:03:22,055 - ERROR - Error in batch 77: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 84 | 
         
            +
            2025-04-02 14:03:22,626 - ERROR - Error in batch 78: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 85 | 
         
            +
            2025-04-02 14:03:22,719 - ERROR - Error in batch 79: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 86 | 
         
            +
            2025-04-02 14:03:22,807 - ERROR - Error in batch 80: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 87 | 
         
            +
            2025-04-02 14:03:22,898 - ERROR - Error in batch 81: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 88 | 
         
            +
            2025-04-02 14:03:23,566 - ERROR - Error in batch 82: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 89 | 
         
            +
            2025-04-02 14:03:23,650 - ERROR - Error in batch 83: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 90 | 
         
            +
            2025-04-02 14:03:23,731 - ERROR - Error in batch 84: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 91 | 
         
            +
            2025-04-02 14:03:23,816 - ERROR - Error in batch 85: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 92 | 
         
            +
            2025-04-02 14:03:24,261 - ERROR - Error in batch 86: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 93 | 
         
            +
            2025-04-02 14:03:24,375 - ERROR - Error in batch 87: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 94 | 
         
            +
            2025-04-02 14:03:24,472 - ERROR - Error in batch 88: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 95 | 
         
            +
            2025-04-02 14:03:24,574 - ERROR - Error in batch 89: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 96 | 
         
            +
            2025-04-02 14:03:24,980 - ERROR - Error in batch 90: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 97 | 
         
            +
            2025-04-02 14:03:25,066 - ERROR - Error in batch 91: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 98 | 
         
            +
            2025-04-02 14:03:25,148 - ERROR - Error in batch 92: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 99 | 
         
            +
            2025-04-02 14:03:25,245 - ERROR - Error in batch 93: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 100 | 
         
            +
            2025-04-02 14:03:25,711 - ERROR - Error in batch 94: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 101 | 
         
            +
            2025-04-02 14:03:25,806 - ERROR - Error in batch 95: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 102 | 
         
            +
            2025-04-02 14:03:25,898 - ERROR - Error in batch 96: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 103 | 
         
            +
            2025-04-02 14:03:26,008 - ERROR - Error in batch 97: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 104 | 
         
            +
            2025-04-02 14:03:26,533 - ERROR - Error in batch 98: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 105 | 
         
            +
            2025-04-02 14:03:26,645 - ERROR - Error in batch 99: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 106 | 
         
            +
            2025-04-02 14:03:26,749 - ERROR - Error in batch 100: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 107 | 
         
            +
            2025-04-02 14:03:26,852 - ERROR - Error in batch 101: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 108 | 
         
            +
            2025-04-02 14:03:27,293 - ERROR - Error in batch 102: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 109 | 
         
            +
            2025-04-02 14:03:27,383 - ERROR - Error in batch 103: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 110 | 
         
            +
            2025-04-02 14:03:27,470 - ERROR - Error in batch 104: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 111 | 
         
            +
            2025-04-02 14:03:27,560 - ERROR - Error in batch 105: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 112 | 
         
            +
            2025-04-02 14:03:28,299 - ERROR - Error in batch 106: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 113 | 
         
            +
            2025-04-02 14:03:28,392 - ERROR - Error in batch 107: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 114 | 
         
            +
            2025-04-02 14:03:28,507 - ERROR - Error in batch 108: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 115 | 
         
            +
            2025-04-02 14:03:28,651 - ERROR - Error in batch 109: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 116 | 
         
            +
            2025-04-02 14:03:29,103 - ERROR - Error in batch 110: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 117 | 
         
            +
            2025-04-02 14:03:29,220 - ERROR - Error in batch 111: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 118 | 
         
            +
            2025-04-02 14:03:29,313 - ERROR - Error in batch 112: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 119 | 
         
            +
            2025-04-02 14:03:29,406 - ERROR - Error in batch 113: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 120 | 
         
            +
            2025-04-02 14:03:29,972 - ERROR - Error in batch 114: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 121 | 
         
            +
            2025-04-02 14:03:30,084 - ERROR - Error in batch 115: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 122 | 
         
            +
            2025-04-02 14:03:30,180 - ERROR - Error in batch 116: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 123 | 
         
            +
            2025-04-02 14:03:30,290 - ERROR - Error in batch 117: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 124 | 
         
            +
            2025-04-02 14:03:31,010 - ERROR - Error in batch 118: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 125 | 
         
            +
            2025-04-02 14:03:31,106 - ERROR - Error in batch 119: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 126 | 
         
            +
            2025-04-02 14:03:31,186 - ERROR - Error in batch 120: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 127 | 
         
            +
            2025-04-02 14:03:31,309 - ERROR - Error in batch 121: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 128 | 
         
            +
            2025-04-02 14:03:31,826 - ERROR - Error in batch 122: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 129 | 
         
            +
            2025-04-02 14:03:31,920 - ERROR - Error in batch 123: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 130 | 
         
            +
            2025-04-02 14:03:32,007 - ERROR - Error in batch 124: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 131 | 
         
            +
            2025-04-02 14:03:32,100 - ERROR - Error in batch 125: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 132 | 
         
            +
            2025-04-02 14:03:32,627 - ERROR - Error in batch 126: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 133 | 
         
            +
            2025-04-02 14:03:32,711 - ERROR - Error in batch 127: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 134 | 
         
            +
            2025-04-02 14:03:32,795 - ERROR - Error in batch 128: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 135 | 
         
            +
            2025-04-02 14:03:32,874 - ERROR - Error in batch 129: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 136 | 
         
            +
            2025-04-02 14:03:33,298 - ERROR - Error in batch 130: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 137 | 
         
            +
            2025-04-02 14:03:33,377 - ERROR - Error in batch 131: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 138 | 
         
            +
            2025-04-02 14:03:33,546 - ERROR - Error in batch 132: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 139 | 
         
            +
            2025-04-02 14:03:33,661 - ERROR - Error in batch 133: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 140 | 
         
            +
            2025-04-02 14:03:34,173 - ERROR - Error in batch 134: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 141 | 
         
            +
            2025-04-02 14:03:34,249 - ERROR - Error in batch 135: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 142 | 
         
            +
            2025-04-02 14:03:34,331 - ERROR - Error in batch 136: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 143 | 
         
            +
            2025-04-02 14:03:34,403 - ERROR - Error in batch 137: shape '[256, 56, 56, 64]' is invalid for input of size 55115776
         
     | 
| 144 | 
         
            +
            2025-04-02 14:03:34,454 - ERROR - Error in batch 138: shape '[40, 56, 56, 64]' is invalid for input of size 8611840
         
     | 
| 145 | 
         
            +
            2025-04-02 14:03:34,859 - INFO - Epoch 1 - Train Loss: 0.0000
         
     | 
| 146 | 
         
            +
            2025-04-02 14:03:42,477 - ERROR - Error during evaluation in epoch 1: shape '[1024, 56, 56, 64]' is invalid for input of size 220463104
         
     | 
| 147 | 
         
            +
            2025-04-02 14:03:42,478 - INFO - Skipping evaluation for this epoch
         
     | 
    	
        exp-rank-16/resnet/fewshot_100_percent/training_20250402-140719.log
    ADDED
    
    | 
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| 1 | 
         
            +
            2025-04-02 14:07:19,177 - INFO - Arguments: Namespace(datasets=['aml', 'fundus', 'mammo_calc', 'mammo_mass', 'pneumonia', 'oct', 'pbc', 'bloodmnist', 'breastmnist', 'octmnist', 'pneumoniamnist', 'retinamnist'], use_corruptions=False, severity_range=[1, 3], corruption_types=None, fewshot=None, epochs=20, batch_size=256, lr=0.0001, weight_decay=0.0001, temperature=2.0, alpha=0.5, backbone='resnet', lora_rank=16, lora_alpha=16, lora_dropout=0.1, device=device(type='cuda', index=6), gpu=6, seed=42, num_workers=4, output_dir='./outputs/exp2/resnet/fewshot_100_percent', log_interval=10, save_interval=1, eval_interval=1, resume=None)
         
     | 
| 2 | 
         
            +
            2025-04-02 14:07:19,178 - INFO - Creating dataloaders for datasets: ['aml', 'fundus', 'mammo_calc', 'mammo_mass', 'pneumonia', 'oct', 'pbc', 'bloodmnist', 'breastmnist', 'octmnist', 'pneumoniamnist', 'retinamnist']
         
     | 
| 3 | 
         
            +
            2025-04-02 14:08:19,350 - INFO - Initializing RobustMedClip model
         
     | 
| 4 | 
         
            +
            2025-04-02 14:08:26,804 - INFO - Starting training
         
     | 
| 5 | 
         
            +
            2025-04-02 14:08:26,804 - INFO - Epoch 1/20
         
     | 
| 6 | 
         
            +
            2025-04-02 14:08:31,497 - INFO - Train Epoch: 1 [0/139 (0%)]	Loss: 4.5219	
         
     | 
| 7 | 
         
            +
            2025-04-02 14:08:39,343 - INFO - Train Epoch: 1 [10/139 (7%)]	Loss: 4.3552	
         
     | 
| 8 | 
         
            +
            2025-04-02 14:08:47,275 - INFO - Train Epoch: 1 [20/139 (14%)]	Loss: 4.3738	
         
     | 
| 9 | 
         
            +
            2025-04-02 14:08:55,259 - INFO - Train Epoch: 1 [30/139 (22%)]	Loss: 4.2367	
         
     | 
| 10 | 
         
            +
            2025-04-02 14:09:03,042 - INFO - Train Epoch: 1 [40/139 (29%)]	Loss: 4.1578	
         
     | 
| 11 | 
         
            +
            2025-04-02 14:09:10,988 - INFO - Train Epoch: 1 [50/139 (36%)]	Loss: 3.9022	
         
     | 
| 12 | 
         
            +
            2025-04-02 14:09:18,920 - INFO - Train Epoch: 1 [60/139 (43%)]	Loss: 3.9384	
         
     | 
| 13 | 
         
            +
            2025-04-02 14:09:26,740 - INFO - Train Epoch: 1 [70/139 (50%)]	Loss: 3.9649	
         
     | 
| 14 | 
         
            +
            2025-04-02 14:09:34,752 - INFO - Train Epoch: 1 [80/139 (58%)]	Loss: 3.9027	
         
     | 
| 15 | 
         
            +
            2025-04-02 14:09:42,769 - INFO - Train Epoch: 1 [90/139 (65%)]	Loss: 3.8656	
         
     | 
| 16 | 
         
            +
            2025-04-02 14:09:50,911 - INFO - Train Epoch: 1 [100/139 (72%)]	Loss: 3.8772	
         
     | 
| 17 | 
         
            +
            2025-04-02 14:09:58,825 - INFO - Train Epoch: 1 [110/139 (79%)]	Loss: 3.8813	
         
     | 
| 18 | 
         
            +
            2025-04-02 14:10:06,646 - INFO - Train Epoch: 1 [120/139 (86%)]	Loss: 3.7529	
         
     | 
| 19 | 
         
            +
            2025-04-02 14:10:14,488 - INFO - Train Epoch: 1 [130/139 (94%)]	Loss: 3.7497	
         
     | 
| 20 | 
         
            +
            2025-04-02 14:10:21,066 - INFO - Epoch 1 - Train Loss: 4.0231
         
     | 
| 21 | 
         
            +
            2025-04-02 14:10:46,829 - INFO - Epoch 1 - Validation Accuracy: 9.82%
         
     | 
| 22 | 
         
            +
            2025-04-02 14:10:46,830 - INFO - New best validation accuracy: 9.82%
         
     | 
| 23 | 
         
            +
            2025-04-02 14:10:48,016 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/best_model
         
     | 
| 24 | 
         
            +
            2025-04-02 14:10:49,090 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
     | 
| 25 | 
         
            +
            2025-04-02 14:10:49,090 - INFO - Epoch 2/20
         
     | 
| 26 | 
         
            +
            2025-04-02 14:10:51,245 - INFO - Train Epoch: 2 [0/139 (0%)]	Loss: 3.7751	
         
     | 
| 27 | 
         
            +
            2025-04-02 14:10:59,118 - INFO - Train Epoch: 2 [10/139 (7%)]	Loss: 3.8226	
         
     | 
| 28 | 
         
            +
            2025-04-02 14:11:07,061 - INFO - Train Epoch: 2 [20/139 (14%)]	Loss: 3.6395	
         
     | 
| 29 | 
         
            +
            2025-04-02 14:11:14,973 - INFO - Train Epoch: 2 [30/139 (22%)]	Loss: 3.6151	
         
     | 
| 30 | 
         
            +
            2025-04-02 14:11:22,881 - INFO - Train Epoch: 2 [40/139 (29%)]	Loss: 3.5845	
         
     | 
| 31 | 
         
            +
            2025-04-02 14:11:30,804 - INFO - Train Epoch: 2 [50/139 (36%)]	Loss: 3.5294	
         
     | 
| 32 | 
         
            +
            2025-04-02 14:11:38,842 - INFO - Train Epoch: 2 [60/139 (43%)]	Loss: 3.5398	
         
     | 
| 33 | 
         
            +
            2025-04-02 14:11:46,763 - INFO - Train Epoch: 2 [70/139 (50%)]	Loss: 3.4746	
         
     | 
| 34 | 
         
            +
            2025-04-02 14:11:54,696 - INFO - Train Epoch: 2 [80/139 (58%)]	Loss: 3.5749	
         
     | 
| 35 | 
         
            +
            2025-04-02 14:12:02,653 - INFO - Train Epoch: 2 [90/139 (65%)]	Loss: 3.4164	
         
     | 
| 36 | 
         
            +
            2025-04-02 14:12:10,649 - INFO - Train Epoch: 2 [100/139 (72%)]	Loss: 3.5414	
         
     | 
| 37 | 
         
            +
            2025-04-02 14:12:18,553 - INFO - Train Epoch: 2 [110/139 (79%)]	Loss: 3.4853	
         
     | 
| 38 | 
         
            +
            2025-04-02 14:12:26,574 - INFO - Train Epoch: 2 [120/139 (86%)]	Loss: 3.4341	
         
     | 
| 39 | 
         
            +
            2025-04-02 14:12:34,505 - INFO - Train Epoch: 2 [130/139 (94%)]	Loss: 3.4379	
         
     | 
| 40 | 
         
            +
            2025-04-02 14:12:40,319 - INFO - Epoch 2 - Train Loss: 3.5353
         
     | 
| 41 | 
         
            +
            2025-04-02 14:13:05,209 - INFO - Epoch 2 - Validation Accuracy: 21.44%
         
     | 
| 42 | 
         
            +
            2025-04-02 14:13:05,210 - INFO - New best validation accuracy: 21.44%
         
     | 
| 43 | 
         
            +
            2025-04-02 14:13:06,652 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/best_model
         
     | 
| 44 | 
         
            +
            2025-04-02 14:13:08,090 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
     | 
| 45 | 
         
            +
            2025-04-02 14:13:08,090 - INFO - Epoch 3/20
         
     | 
| 46 | 
         
            +
            2025-04-02 14:13:10,400 - INFO - Train Epoch: 3 [0/139 (0%)]	Loss: 3.3996	
         
     | 
| 47 | 
         
            +
            2025-04-02 14:13:18,340 - INFO - Train Epoch: 3 [10/139 (7%)]	Loss: 3.3734	
         
     | 
| 48 | 
         
            +
            2025-04-02 14:13:26,104 - INFO - Train Epoch: 3 [20/139 (14%)]	Loss: 3.2506	
         
     | 
| 49 | 
         
            +
            2025-04-02 14:13:33,974 - INFO - Train Epoch: 3 [30/139 (22%)]	Loss: 3.3017	
         
     | 
| 50 | 
         
            +
            2025-04-02 14:13:41,905 - INFO - Train Epoch: 3 [40/139 (29%)]	Loss: 3.1492	
         
     | 
| 51 | 
         
            +
            2025-04-02 14:13:49,857 - INFO - Train Epoch: 3 [50/139 (36%)]	Loss: 3.2096	
         
     | 
| 52 | 
         
            +
            2025-04-02 14:13:57,756 - INFO - Train Epoch: 3 [60/139 (43%)]	Loss: 3.2739	
         
     | 
| 53 | 
         
            +
            2025-04-02 14:14:05,683 - INFO - Train Epoch: 3 [70/139 (50%)]	Loss: 3.3441	
         
     | 
| 54 | 
         
            +
            2025-04-02 14:14:13,628 - INFO - Train Epoch: 3 [80/139 (58%)]	Loss: 3.1666	
         
     | 
| 55 | 
         
            +
            2025-04-02 14:14:21,538 - INFO - Train Epoch: 3 [90/139 (65%)]	Loss: 3.1848	
         
     | 
| 56 | 
         
            +
            2025-04-02 14:14:29,425 - INFO - Train Epoch: 3 [100/139 (72%)]	Loss: 3.1620	
         
     | 
| 57 | 
         
            +
            2025-04-02 14:14:37,312 - INFO - Train Epoch: 3 [110/139 (79%)]	Loss: 3.2047	
         
     | 
| 58 | 
         
            +
            2025-04-02 14:14:45,224 - INFO - Train Epoch: 3 [120/139 (86%)]	Loss: 3.1099	
         
     | 
| 59 | 
         
            +
            2025-04-02 14:14:53,154 - INFO - Train Epoch: 3 [130/139 (94%)]	Loss: 3.1229	
         
     | 
| 60 | 
         
            +
            2025-04-02 14:14:59,087 - INFO - Epoch 3 - Train Loss: 3.2229
         
     | 
| 61 | 
         
            +
            2025-04-02 14:15:24,308 - INFO - Epoch 3 - Validation Accuracy: 23.85%
         
     | 
| 62 | 
         
            +
            2025-04-02 14:15:24,309 - INFO - New best validation accuracy: 23.85%
         
     | 
| 63 | 
         
            +
            2025-04-02 14:15:25,884 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/best_model
         
     | 
| 64 | 
         
            +
            2025-04-02 14:15:27,427 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
     | 
| 65 | 
         
            +
            2025-04-02 14:15:27,427 - INFO - Epoch 4/20
         
     | 
| 66 | 
         
            +
            2025-04-02 14:15:29,480 - INFO - Train Epoch: 4 [0/139 (0%)]	Loss: 3.0476	
         
     | 
| 67 | 
         
            +
            2025-04-02 14:15:37,446 - INFO - Train Epoch: 4 [10/139 (7%)]	Loss: 3.1307	
         
     | 
| 68 | 
         
            +
            2025-04-02 14:15:45,516 - INFO - Train Epoch: 4 [20/139 (14%)]	Loss: 3.0492	
         
     | 
| 69 | 
         
            +
            2025-04-02 14:15:53,644 - INFO - Train Epoch: 4 [30/139 (22%)]	Loss: 3.0015	
         
     | 
| 70 | 
         
            +
            2025-04-02 14:16:01,736 - INFO - Train Epoch: 4 [40/139 (29%)]	Loss: 3.0253	
         
     | 
| 71 | 
         
            +
            2025-04-02 14:16:09,682 - INFO - Train Epoch: 4 [50/139 (36%)]	Loss: 2.9705	
         
     | 
| 72 | 
         
            +
            2025-04-02 14:16:17,814 - INFO - Train Epoch: 4 [60/139 (43%)]	Loss: 2.9053	
         
     | 
| 73 | 
         
            +
            2025-04-02 14:16:26,071 - INFO - Train Epoch: 4 [70/139 (50%)]	Loss: 2.9070	
         
     | 
| 74 | 
         
            +
            2025-04-02 14:16:34,152 - INFO - Train Epoch: 4 [80/139 (58%)]	Loss: 2.9836	
         
     | 
| 75 | 
         
            +
            2025-04-02 14:16:42,088 - INFO - Train Epoch: 4 [90/139 (65%)]	Loss: 2.8902	
         
     | 
| 76 | 
         
            +
            2025-04-02 14:16:50,075 - INFO - Train Epoch: 4 [100/139 (72%)]	Loss: 2.9173	
         
     | 
| 77 | 
         
            +
            2025-04-02 14:16:58,008 - INFO - Train Epoch: 4 [110/139 (79%)]	Loss: 2.8690	
         
     | 
| 78 | 
         
            +
            2025-04-02 14:17:06,092 - INFO - Train Epoch: 4 [120/139 (86%)]	Loss: 2.9113	
         
     | 
| 79 | 
         
            +
            2025-04-02 14:17:13,980 - INFO - Train Epoch: 4 [130/139 (94%)]	Loss: 2.8097	
         
     | 
| 80 | 
         
            +
            2025-04-02 14:17:19,803 - INFO - Epoch 4 - Train Loss: 2.9747
         
     | 
| 81 | 
         
            +
            2025-04-02 14:17:44,481 - INFO - Epoch 4 - Validation Accuracy: 27.90%
         
     | 
| 82 | 
         
            +
            2025-04-02 14:17:44,482 - INFO - New best validation accuracy: 27.90%
         
     | 
| 83 | 
         
            +
            2025-04-02 14:17:45,879 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/best_model
         
     | 
| 84 | 
         
            +
            2025-04-02 14:17:47,361 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
     | 
| 85 | 
         
            +
            2025-04-02 14:17:47,361 - INFO - Epoch 5/20
         
     | 
| 86 | 
         
            +
            2025-04-02 14:17:49,444 - INFO - Train Epoch: 5 [0/139 (0%)]	Loss: 2.8019	
         
     | 
| 87 | 
         
            +
            2025-04-02 14:17:57,296 - INFO - Train Epoch: 5 [10/139 (7%)]	Loss: 2.8872	
         
     | 
| 88 | 
         
            +
            2025-04-02 14:18:05,089 - INFO - Train Epoch: 5 [20/139 (14%)]	Loss: 2.7613	
         
     | 
| 89 | 
         
            +
            2025-04-02 14:18:13,036 - INFO - Train Epoch: 5 [30/139 (22%)]	Loss: 2.8889	
         
     | 
| 90 | 
         
            +
            2025-04-02 14:18:20,921 - INFO - Train Epoch: 5 [40/139 (29%)]	Loss: 2.9032	
         
     | 
| 91 | 
         
            +
            2025-04-02 14:18:28,814 - INFO - Train Epoch: 5 [50/139 (36%)]	Loss: 2.8039	
         
     | 
| 92 | 
         
            +
            2025-04-02 14:18:36,766 - INFO - Train Epoch: 5 [60/139 (43%)]	Loss: 2.8803	
         
     | 
| 93 | 
         
            +
            2025-04-02 14:18:44,655 - INFO - Train Epoch: 5 [70/139 (50%)]	Loss: 2.7702	
         
     | 
| 94 | 
         
            +
            2025-04-02 14:18:52,577 - INFO - Train Epoch: 5 [80/139 (58%)]	Loss: 2.7873	
         
     | 
| 95 | 
         
            +
            2025-04-02 14:19:00,457 - INFO - Train Epoch: 5 [90/139 (65%)]	Loss: 2.7544	
         
     | 
| 96 | 
         
            +
            2025-04-02 14:19:08,336 - INFO - Train Epoch: 5 [100/139 (72%)]	Loss: 2.6804	
         
     | 
| 97 | 
         
            +
            2025-04-02 14:19:16,275 - INFO - Train Epoch: 5 [110/139 (79%)]	Loss: 2.7358	
         
     | 
| 98 | 
         
            +
            2025-04-02 14:19:24,248 - INFO - Train Epoch: 5 [120/139 (86%)]	Loss: 2.6353	
         
     | 
| 99 | 
         
            +
            2025-04-02 14:19:32,123 - INFO - Train Epoch: 5 [130/139 (94%)]	Loss: 2.6576	
         
     | 
| 100 | 
         
            +
            2025-04-02 14:19:37,942 - INFO - Epoch 5 - Train Loss: 2.7928
         
     | 
| 101 | 
         
            +
            2025-04-02 14:20:02,827 - INFO - Epoch 5 - Validation Accuracy: 27.45%
         
     | 
| 102 | 
         
            +
            2025-04-02 14:20:04,121 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
     | 
| 103 | 
         
            +
            2025-04-02 14:20:04,121 - INFO - Epoch 6/20
         
     | 
| 104 | 
         
            +
            2025-04-02 14:20:05,983 - INFO - Train Epoch: 6 [0/139 (0%)]	Loss: 2.7246	
         
     | 
| 105 | 
         
            +
            2025-04-02 14:20:13,820 - INFO - Train Epoch: 6 [10/139 (7%)]	Loss: 2.6457	
         
     | 
| 106 | 
         
            +
            2025-04-02 14:20:21,745 - INFO - Train Epoch: 6 [20/139 (14%)]	Loss: 2.6588	
         
     | 
| 107 | 
         
            +
            2025-04-02 14:20:29,627 - INFO - Train Epoch: 6 [30/139 (22%)]	Loss: 2.6471	
         
     | 
| 108 | 
         
            +
            2025-04-02 14:20:37,522 - INFO - Train Epoch: 6 [40/139 (29%)]	Loss: 2.6302	
         
     | 
| 109 | 
         
            +
            2025-04-02 14:20:45,427 - INFO - Train Epoch: 6 [50/139 (36%)]	Loss: 2.6366	
         
     | 
| 110 | 
         
            +
            2025-04-02 14:20:53,308 - INFO - Train Epoch: 6 [60/139 (43%)]	Loss: 2.6963	
         
     | 
| 111 | 
         
            +
            2025-04-02 14:21:01,308 - INFO - Train Epoch: 6 [70/139 (50%)]	Loss: 2.5931	
         
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            2025-04-02 14:21:09,185 - INFO - Train Epoch: 6 [80/139 (58%)]	Loss: 2.6493	
         
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            2025-04-02 14:21:17,339 - INFO - Train Epoch: 6 [90/139 (65%)]	Loss: 2.6008	
         
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            2025-04-02 14:21:25,325 - INFO - Train Epoch: 6 [100/139 (72%)]	Loss: 2.5623	
         
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            2025-04-02 14:21:33,239 - INFO - Train Epoch: 6 [110/139 (79%)]	Loss: 2.5385	
         
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            2025-04-02 14:21:41,193 - INFO - Train Epoch: 6 [120/139 (86%)]	Loss: 2.6009	
         
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            2025-04-02 14:21:49,147 - INFO - Train Epoch: 6 [130/139 (94%)]	Loss: 2.6881	
         
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            2025-04-02 14:21:55,137 - INFO - Epoch 6 - Train Loss: 2.6606
         
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            2025-04-02 14:22:19,943 - INFO - Epoch 6 - Validation Accuracy: 28.41%
         
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            2025-04-02 14:22:19,943 - INFO - New best validation accuracy: 28.41%
         
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            2025-04-02 14:22:21,111 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/best_model
         
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            2025-04-02 14:22:22,358 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
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            2025-04-02 14:22:22,358 - INFO - Epoch 7/20
         
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            2025-04-02 14:22:24,615 - INFO - Train Epoch: 7 [0/139 (0%)]	Loss: 2.5360	
         
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            2025-04-02 14:22:32,474 - INFO - Train Epoch: 7 [10/139 (7%)]	Loss: 2.5638	
         
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            2025-04-02 14:22:40,356 - INFO - Train Epoch: 7 [20/139 (14%)]	Loss: 2.5746	
         
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            2025-04-02 14:22:48,327 - INFO - Train Epoch: 7 [30/139 (22%)]	Loss: 2.6330	
         
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            2025-04-02 14:22:56,226 - INFO - Train Epoch: 7 [40/139 (29%)]	Loss: 2.6069	
         
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            2025-04-02 14:23:12,169 - INFO - Train Epoch: 7 [60/139 (43%)]	Loss: 2.5539	
         
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            2025-04-02 14:23:20,235 - INFO - Train Epoch: 7 [70/139 (50%)]	Loss: 2.5554	
         
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            2025-04-02 14:23:28,198 - INFO - Train Epoch: 7 [80/139 (58%)]	Loss: 2.4784	
         
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            2025-04-02 14:23:36,143 - INFO - Train Epoch: 7 [90/139 (65%)]	Loss: 2.4287	
         
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            2025-04-02 14:23:44,058 - INFO - Train Epoch: 7 [100/139 (72%)]	Loss: 2.6228	
         
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            2025-04-02 14:23:52,034 - INFO - Train Epoch: 7 [110/139 (79%)]	Loss: 2.4963	
         
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            2025-04-02 14:23:59,989 - INFO - Train Epoch: 7 [120/139 (86%)]	Loss: 2.5964	
         
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            2025-04-02 14:24:07,921 - INFO - Train Epoch: 7 [130/139 (94%)]	Loss: 2.6629	
         
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            2025-04-02 14:24:13,768 - INFO - Epoch 7 - Train Loss: 2.5792
         
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            2025-04-02 14:24:39,020 - INFO - Epoch 7 - Validation Accuracy: 29.49%
         
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            2025-04-02 14:24:39,022 - INFO - New best validation accuracy: 29.49%
         
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            +
            2025-04-02 14:24:40,351 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/best_model
         
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            2025-04-02 14:24:41,715 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
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            2025-04-02 14:24:41,716 - INFO - Epoch 8/20
         
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            2025-04-02 14:24:43,661 - INFO - Train Epoch: 8 [0/139 (0%)]	Loss: 2.6087	
         
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            2025-04-02 14:24:51,652 - INFO - Train Epoch: 8 [10/139 (7%)]	Loss: 2.5279	
         
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            2025-04-02 14:24:59,544 - INFO - Train Epoch: 8 [20/139 (14%)]	Loss: 2.5207	
         
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            2025-04-02 14:25:07,593 - INFO - Train Epoch: 8 [30/139 (22%)]	Loss: 2.5255	
         
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            2025-04-02 14:25:15,378 - INFO - Train Epoch: 8 [40/139 (29%)]	Loss: 2.5060	
         
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            2025-04-02 14:25:23,287 - INFO - Train Epoch: 8 [50/139 (36%)]	Loss: 2.4811	
         
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            2025-04-02 14:25:31,151 - INFO - Train Epoch: 8 [60/139 (43%)]	Loss: 2.5239	
         
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            2025-04-02 14:25:38,985 - INFO - Train Epoch: 8 [70/139 (50%)]	Loss: 2.4759	
         
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            2025-04-02 14:25:46,802 - INFO - Train Epoch: 8 [80/139 (58%)]	Loss: 2.6370	
         
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            2025-04-02 14:25:54,785 - INFO - Train Epoch: 8 [90/139 (65%)]	Loss: 2.5335	
         
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            2025-04-02 14:26:02,624 - INFO - Train Epoch: 8 [100/139 (72%)]	Loss: 2.4911	
         
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            2025-04-02 14:26:10,570 - INFO - Train Epoch: 8 [110/139 (79%)]	Loss: 2.5112	
         
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            2025-04-02 14:26:18,575 - INFO - Train Epoch: 8 [120/139 (86%)]	Loss: 2.4290	
         
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            2025-04-02 14:26:26,461 - INFO - Train Epoch: 8 [130/139 (94%)]	Loss: 2.5473	
         
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            +
            2025-04-02 14:26:32,242 - INFO - Epoch 8 - Train Loss: 2.5068
         
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            +
            2025-04-02 14:26:57,435 - INFO - Epoch 8 - Validation Accuracy: 31.17%
         
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            +
            2025-04-02 14:26:57,436 - INFO - New best validation accuracy: 31.17%
         
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            +
            2025-04-02 14:26:58,947 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/best_model
         
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            2025-04-02 14:27:00,206 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
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            2025-04-02 14:27:00,207 - INFO - Epoch 9/20
         
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            +
            2025-04-02 14:27:02,778 - INFO - Train Epoch: 9 [0/139 (0%)]	Loss: 2.5377	
         
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            +
            2025-04-02 14:27:10,569 - INFO - Train Epoch: 9 [10/139 (7%)]	Loss: 2.4340	
         
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            2025-04-02 14:27:18,373 - INFO - Train Epoch: 9 [20/139 (14%)]	Loss: 2.4468	
         
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            +
            2025-04-02 14:27:26,329 - INFO - Train Epoch: 9 [30/139 (22%)]	Loss: 2.4994	
         
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            2025-04-02 14:27:34,247 - INFO - Train Epoch: 9 [40/139 (29%)]	Loss: 2.2930	
         
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            2025-04-02 14:27:42,104 - INFO - Train Epoch: 9 [50/139 (36%)]	Loss: 2.4001	
         
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            2025-04-02 14:27:49,982 - INFO - Train Epoch: 9 [60/139 (43%)]	Loss: 2.4157	
         
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            2025-04-02 14:27:57,895 - INFO - Train Epoch: 9 [70/139 (50%)]	Loss: 2.4382	
         
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            2025-04-02 14:28:05,796 - INFO - Train Epoch: 9 [80/139 (58%)]	Loss: 2.5183	
         
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            2025-04-02 14:28:13,747 - INFO - Train Epoch: 9 [90/139 (65%)]	Loss: 2.2623	
         
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            +
            2025-04-02 14:28:21,760 - INFO - Train Epoch: 9 [100/139 (72%)]	Loss: 2.3935	
         
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            +
            2025-04-02 14:28:29,686 - INFO - Train Epoch: 9 [110/139 (79%)]	Loss: 2.3338	
         
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            +
            2025-04-02 14:28:37,765 - INFO - Train Epoch: 9 [120/139 (86%)]	Loss: 2.4298	
         
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            2025-04-02 14:28:45,919 - INFO - Train Epoch: 9 [130/139 (94%)]	Loss: 2.5325	
         
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            +
            2025-04-02 14:28:51,887 - INFO - Epoch 9 - Train Loss: 2.4299
         
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            +
            2025-04-02 14:29:17,795 - INFO - Epoch 9 - Validation Accuracy: 34.27%
         
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            +
            2025-04-02 14:29:17,795 - INFO - New best validation accuracy: 34.27%
         
     | 
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            +
            2025-04-02 14:29:19,677 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/best_model
         
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            2025-04-02 14:29:21,016 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-02 14:29:21,017 - INFO - Epoch 10/20
         
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            +
            2025-04-02 14:29:23,062 - INFO - Train Epoch: 10 [0/139 (0%)]	Loss: 2.3259	
         
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            +
            2025-04-02 14:29:30,893 - INFO - Train Epoch: 10 [10/139 (7%)]	Loss: 2.3142	
         
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            +
            2025-04-02 14:29:38,760 - INFO - Train Epoch: 10 [20/139 (14%)]	Loss: 2.4074	
         
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            +
            2025-04-02 14:29:46,599 - INFO - Train Epoch: 10 [30/139 (22%)]	Loss: 2.3068	
         
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            2025-04-02 14:29:54,705 - INFO - Train Epoch: 10 [40/139 (29%)]	Loss: 2.4340	
         
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            2025-04-02 14:30:02,641 - INFO - Train Epoch: 10 [50/139 (36%)]	Loss: 2.3323	
         
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            +
            2025-04-02 14:30:10,596 - INFO - Train Epoch: 10 [60/139 (43%)]	Loss: 2.4857	
         
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            +
            2025-04-02 14:30:18,597 - INFO - Train Epoch: 10 [70/139 (50%)]	Loss: 2.3940	
         
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            2025-04-02 14:30:26,574 - INFO - Train Epoch: 10 [80/139 (58%)]	Loss: 2.3198	
         
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            2025-04-02 14:30:34,548 - INFO - Train Epoch: 10 [90/139 (65%)]	Loss: 2.2988	
         
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            +
            2025-04-02 14:30:42,457 - INFO - Train Epoch: 10 [100/139 (72%)]	Loss: 2.3701	
         
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            +
            2025-04-02 14:30:50,343 - INFO - Train Epoch: 10 [110/139 (79%)]	Loss: 2.4003	
         
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            +
            2025-04-02 14:30:58,453 - INFO - Train Epoch: 10 [120/139 (86%)]	Loss: 2.2462	
         
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            2025-04-02 14:31:06,332 - INFO - Train Epoch: 10 [130/139 (94%)]	Loss: 2.3415	
         
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            +
            2025-04-02 14:31:12,202 - INFO - Epoch 10 - Train Loss: 2.3389
         
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            +
            2025-04-02 14:31:38,925 - INFO - Epoch 10 - Validation Accuracy: 33.31%
         
     | 
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            +
            2025-04-02 14:31:40,435 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-02 14:31:40,436 - INFO - Epoch 11/20
         
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            +
            2025-04-02 14:31:42,480 - INFO - Train Epoch: 11 [0/139 (0%)]	Loss: 2.2654	
         
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            +
            2025-04-02 14:31:50,346 - INFO - Train Epoch: 11 [10/139 (7%)]	Loss: 2.2970	
         
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            2025-04-02 14:31:58,473 - INFO - Train Epoch: 11 [20/139 (14%)]	Loss: 2.3045	
         
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            +
            2025-04-02 14:32:06,487 - INFO - Train Epoch: 11 [30/139 (22%)]	Loss: 2.3527	
         
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            2025-04-02 14:32:14,756 - INFO - Train Epoch: 11 [40/139 (29%)]	Loss: 2.2589	
         
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            2025-04-02 14:32:22,860 - INFO - Train Epoch: 11 [50/139 (36%)]	Loss: 2.2087	
         
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            2025-04-02 14:32:31,009 - INFO - Train Epoch: 11 [60/139 (43%)]	Loss: 2.3182	
         
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            +
            2025-04-02 14:32:39,060 - INFO - Train Epoch: 11 [70/139 (50%)]	Loss: 2.1821	
         
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            2025-04-02 14:32:47,174 - INFO - Train Epoch: 11 [80/139 (58%)]	Loss: 2.2515	
         
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            2025-04-02 14:32:55,311 - INFO - Train Epoch: 11 [90/139 (65%)]	Loss: 2.2542	
         
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            2025-04-02 14:33:03,449 - INFO - Train Epoch: 11 [100/139 (72%)]	Loss: 2.1972	
         
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            +
            2025-04-02 14:33:11,523 - INFO - Train Epoch: 11 [110/139 (79%)]	Loss: 2.2127	
         
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            +
            2025-04-02 14:33:19,549 - INFO - Train Epoch: 11 [120/139 (86%)]	Loss: 2.2104	
         
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            2025-04-02 14:33:27,721 - INFO - Train Epoch: 11 [130/139 (94%)]	Loss: 2.2698	
         
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            +
            2025-04-02 14:33:33,917 - INFO - Epoch 11 - Train Loss: 2.2597
         
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            +
            2025-04-02 14:34:00,394 - INFO - Epoch 11 - Validation Accuracy: 37.89%
         
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| 218 | 
         
            +
            2025-04-02 14:34:00,394 - INFO - New best validation accuracy: 37.89%
         
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            +
            2025-04-02 14:34:02,390 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/best_model
         
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            2025-04-02 14:34:03,646 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-02 14:34:03,646 - INFO - Epoch 12/20
         
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            +
            2025-04-02 14:34:06,077 - INFO - Train Epoch: 12 [0/139 (0%)]	Loss: 2.1203	
         
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            +
            2025-04-02 14:34:14,016 - INFO - Train Epoch: 12 [10/139 (7%)]	Loss: 2.2320	
         
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            2025-04-02 14:34:22,078 - INFO - Train Epoch: 12 [20/139 (14%)]	Loss: 2.2467	
         
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            +
            2025-04-02 14:34:30,304 - INFO - Train Epoch: 12 [30/139 (22%)]	Loss: 2.1849	
         
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            2025-04-02 14:34:38,305 - INFO - Train Epoch: 12 [40/139 (29%)]	Loss: 2.2505	
         
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            +
            2025-04-02 14:34:46,333 - INFO - Train Epoch: 12 [50/139 (36%)]	Loss: 2.2347	
         
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            +
            2025-04-02 14:34:54,549 - INFO - Train Epoch: 12 [60/139 (43%)]	Loss: 2.1159	
         
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            +
            2025-04-02 14:35:02,640 - INFO - Train Epoch: 12 [70/139 (50%)]	Loss: 2.2158	
         
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            2025-04-02 14:35:10,613 - INFO - Train Epoch: 12 [80/139 (58%)]	Loss: 2.2528	
         
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            +
            2025-04-02 14:35:18,586 - INFO - Train Epoch: 12 [90/139 (65%)]	Loss: 2.2577	
         
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            +
            2025-04-02 14:35:26,673 - INFO - Train Epoch: 12 [100/139 (72%)]	Loss: 2.2492	
         
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            2025-04-02 14:35:34,945 - INFO - Train Epoch: 12 [110/139 (79%)]	Loss: 2.1906	
         
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            +
            2025-04-02 14:35:43,052 - INFO - Train Epoch: 12 [120/139 (86%)]	Loss: 2.1317	
         
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            +
            2025-04-02 14:35:51,028 - INFO - Train Epoch: 12 [130/139 (94%)]	Loss: 2.2154	
         
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            +
            2025-04-02 14:35:56,978 - INFO - Epoch 12 - Train Loss: 2.2076
         
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            +
            2025-04-02 14:36:23,137 - INFO - Epoch 12 - Validation Accuracy: 37.75%
         
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            +
            2025-04-02 14:36:24,306 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-02 14:36:24,306 - INFO - Epoch 13/20
         
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            +
            2025-04-02 14:36:26,469 - INFO - Train Epoch: 13 [0/139 (0%)]	Loss: 2.2942	
         
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            +
            2025-04-02 14:36:34,691 - INFO - Train Epoch: 13 [10/139 (7%)]	Loss: 2.1990	
         
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            +
            2025-04-02 14:36:43,071 - INFO - Train Epoch: 13 [20/139 (14%)]	Loss: 2.2838	
         
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            +
            2025-04-02 14:36:51,320 - INFO - Train Epoch: 13 [30/139 (22%)]	Loss: 2.1040	
         
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            +
            2025-04-02 14:36:59,453 - INFO - Train Epoch: 13 [40/139 (29%)]	Loss: 2.1719	
         
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            +
            2025-04-02 14:37:07,562 - INFO - Train Epoch: 13 [50/139 (36%)]	Loss: 2.3142	
         
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            +
            2025-04-02 14:37:15,538 - INFO - Train Epoch: 13 [60/139 (43%)]	Loss: 2.1971	
         
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            +
            2025-04-02 14:37:23,899 - INFO - Train Epoch: 13 [70/139 (50%)]	Loss: 2.1866	
         
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            +
            2025-04-02 14:37:31,914 - INFO - Train Epoch: 13 [80/139 (58%)]	Loss: 2.0487	
         
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            +
            2025-04-02 14:37:40,043 - INFO - Train Epoch: 13 [90/139 (65%)]	Loss: 2.1672	
         
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            +
            2025-04-02 14:37:48,191 - INFO - Train Epoch: 13 [100/139 (72%)]	Loss: 2.2421	
         
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            +
            2025-04-02 14:37:56,331 - INFO - Train Epoch: 13 [110/139 (79%)]	Loss: 2.2110	
         
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            +
            2025-04-02 14:38:04,329 - INFO - Train Epoch: 13 [120/139 (86%)]	Loss: 2.1149	
         
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            +
            2025-04-02 14:38:12,589 - INFO - Train Epoch: 13 [130/139 (94%)]	Loss: 2.2597	
         
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            +
            2025-04-02 14:38:18,562 - INFO - Epoch 13 - Train Loss: 2.1678
         
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            +
            2025-04-02 14:38:43,817 - INFO - Epoch 13 - Validation Accuracy: 38.39%
         
     | 
| 256 | 
         
            +
            2025-04-02 14:38:43,817 - INFO - New best validation accuracy: 38.39%
         
     | 
| 257 | 
         
            +
            2025-04-02 14:38:45,966 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/best_model
         
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            +
            2025-04-02 14:38:47,453 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
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            2025-04-02 14:41:07,876 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/best_model
         
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            2025-04-02 14:41:09,234 - INFO - Epoch 15/20
         
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            2025-04-02 14:43:00,090 - INFO - Epoch 15 - Train Loss: 2.1101
         
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            2025-04-02 14:43:23,852 - INFO - New best validation accuracy: 41.25%
         
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            2025-04-02 14:43:25,786 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/best_model
         
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            2025-04-02 14:43:27,464 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
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            2025-04-02 14:43:27,464 - INFO - Epoch 16/20
         
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            2025-04-02 14:43:29,743 - INFO - Train Epoch: 16 [0/139 (0%)]	Loss: 2.1173	
         
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            2025-04-02 14:45:11,718 - INFO - Train Epoch: 16 [130/139 (94%)]	Loss: 2.0961	
         
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            2025-04-02 14:45:17,428 - INFO - Epoch 16 - Train Loss: 2.0878
         
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            2025-04-02 14:45:41,506 - INFO - Epoch 16 - Validation Accuracy: 41.72%
         
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            2025-04-02 14:45:41,506 - INFO - New best validation accuracy: 41.72%
         
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            2025-04-02 14:45:43,591 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/best_model
         
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            2025-04-02 14:45:44,981 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
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            2025-04-02 14:45:44,981 - INFO - Epoch 17/20
         
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            2025-04-02 14:45:47,395 - INFO - Train Epoch: 17 [0/139 (0%)]	Loss: 1.9595	
         
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            2025-04-02 14:46:57,764 - INFO - Train Epoch: 17 [90/139 (65%)]	Loss: 2.0375	
         
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            2025-04-02 14:47:05,639 - INFO - Train Epoch: 17 [100/139 (72%)]	Loss: 1.9852	
         
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            2025-04-02 14:47:21,270 - INFO - Train Epoch: 17 [120/139 (86%)]	Loss: 2.0180	
         
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            2025-04-02 14:47:29,100 - INFO - Train Epoch: 17 [130/139 (94%)]	Loss: 2.0758	
         
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            +
            2025-04-02 14:47:34,823 - INFO - Epoch 17 - Train Loss: 2.0673
         
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            2025-04-02 14:47:58,370 - INFO - Epoch 17 - Validation Accuracy: 41.19%
         
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            +
            2025-04-02 14:47:59,761 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
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            2025-04-02 14:47:59,761 - INFO - Epoch 18/20
         
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            2025-04-02 14:48:01,814 - INFO - Train Epoch: 18 [0/139 (0%)]	Loss: 2.1478	
         
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            2025-04-02 14:48:09,665 - INFO - Train Epoch: 18 [10/139 (7%)]	Loss: 2.0207	
         
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            2025-04-02 14:48:17,355 - INFO - Train Epoch: 18 [20/139 (14%)]	Loss: 2.0788	
         
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            2025-04-02 14:48:25,267 - INFO - Train Epoch: 18 [30/139 (22%)]	Loss: 2.1084	
         
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            2025-04-02 14:48:33,026 - INFO - Train Epoch: 18 [40/139 (29%)]	Loss: 1.9776	
         
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            2025-04-02 14:48:40,985 - INFO - Train Epoch: 18 [50/139 (36%)]	Loss: 2.0759	
         
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            2025-04-02 14:48:48,809 - INFO - Train Epoch: 18 [60/139 (43%)]	Loss: 1.9244	
         
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            2025-04-02 14:48:56,743 - INFO - Train Epoch: 18 [70/139 (50%)]	Loss: 2.1015	
         
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            2025-04-02 14:49:04,737 - INFO - Train Epoch: 18 [80/139 (58%)]	Loss: 1.9120	
         
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            2025-04-02 14:49:12,708 - INFO - Train Epoch: 18 [90/139 (65%)]	Loss: 1.9957	
         
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            2025-04-02 14:49:20,710 - INFO - Train Epoch: 18 [100/139 (72%)]	Loss: 2.0247	
         
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            2025-04-02 14:49:28,589 - INFO - Train Epoch: 18 [110/139 (79%)]	Loss: 1.9843	
         
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            2025-04-02 14:49:36,448 - INFO - Train Epoch: 18 [120/139 (86%)]	Loss: 2.0736	
         
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            2025-04-02 14:49:44,284 - INFO - Train Epoch: 18 [130/139 (94%)]	Loss: 1.9569	
         
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            2025-04-02 14:49:50,135 - INFO - Epoch 18 - Train Loss: 2.0515
         
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            +
            2025-04-02 14:50:14,383 - INFO - Epoch 18 - Validation Accuracy: 41.14%
         
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            +
            2025-04-02 14:50:15,836 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-02 14:50:15,836 - INFO - Epoch 19/20
         
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            +
            2025-04-02 14:50:17,955 - INFO - Train Epoch: 19 [0/139 (0%)]	Loss: 2.1049	
         
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            2025-04-02 14:50:25,843 - INFO - Train Epoch: 19 [10/139 (7%)]	Loss: 2.0481	
         
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            2025-04-02 14:50:33,875 - INFO - Train Epoch: 19 [20/139 (14%)]	Loss: 2.0734	
         
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            2025-04-02 14:50:49,936 - INFO - Train Epoch: 19 [40/139 (29%)]	Loss: 2.0199	
         
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            2025-04-02 14:50:57,905 - INFO - Train Epoch: 19 [50/139 (36%)]	Loss: 2.0320	
         
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            2025-04-02 14:51:05,830 - INFO - Train Epoch: 19 [60/139 (43%)]	Loss: 2.0463	
         
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            2025-04-02 14:51:13,752 - INFO - Train Epoch: 19 [70/139 (50%)]	Loss: 2.1244	
         
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            +
            2025-04-02 14:51:21,593 - INFO - Train Epoch: 19 [80/139 (58%)]	Loss: 2.0427	
         
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            +
            2025-04-02 14:51:29,646 - INFO - Train Epoch: 19 [90/139 (65%)]	Loss: 2.0550	
         
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            2025-04-02 14:51:37,536 - INFO - Train Epoch: 19 [100/139 (72%)]	Loss: 2.0762	
         
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            2025-04-02 14:51:45,373 - INFO - Train Epoch: 19 [110/139 (79%)]	Loss: 2.0074	
         
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            +
            2025-04-02 14:51:53,254 - INFO - Train Epoch: 19 [120/139 (86%)]	Loss: 1.9832	
         
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            2025-04-02 14:52:01,088 - INFO - Train Epoch: 19 [130/139 (94%)]	Loss: 2.0020	
         
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            +
            2025-04-02 14:52:06,872 - INFO - Epoch 19 - Train Loss: 2.0318
         
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            2025-04-02 14:52:31,135 - INFO - Epoch 19 - Validation Accuracy: 41.17%
         
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            +
            2025-04-02 14:52:32,456 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
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            2025-04-02 14:52:32,456 - INFO - Epoch 20/20
         
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            2025-04-02 14:52:34,827 - INFO - Train Epoch: 20 [0/139 (0%)]	Loss: 1.9814	
         
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            2025-04-02 14:52:42,642 - INFO - Train Epoch: 20 [10/139 (7%)]	Loss: 1.9657	
         
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            +
            2025-04-02 14:52:50,641 - INFO - Train Epoch: 20 [20/139 (14%)]	Loss: 2.1401	
         
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            +
            2025-04-02 14:52:58,656 - INFO - Train Epoch: 20 [30/139 (22%)]	Loss: 2.0245	
         
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            +
            2025-04-02 14:53:06,422 - INFO - Train Epoch: 20 [40/139 (29%)]	Loss: 1.9865	
         
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            +
            2025-04-02 14:53:14,289 - INFO - Train Epoch: 20 [50/139 (36%)]	Loss: 2.0353	
         
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            +
            2025-04-02 14:53:22,056 - INFO - Train Epoch: 20 [60/139 (43%)]	Loss: 2.0007	
         
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            +
            2025-04-02 14:53:29,894 - INFO - Train Epoch: 20 [70/139 (50%)]	Loss: 2.1748	
         
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            +
            2025-04-02 14:53:37,970 - INFO - Train Epoch: 20 [80/139 (58%)]	Loss: 1.9197	
         
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            +
            2025-04-02 14:53:45,883 - INFO - Train Epoch: 20 [90/139 (65%)]	Loss: 1.9123	
         
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            2025-04-02 14:53:54,097 - INFO - Train Epoch: 20 [100/139 (72%)]	Loss: 2.0517	
         
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            +
            2025-04-02 14:54:02,098 - INFO - Train Epoch: 20 [110/139 (79%)]	Loss: 2.0897	
         
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            +
            2025-04-02 14:54:09,889 - INFO - Train Epoch: 20 [120/139 (86%)]	Loss: 2.0286	
         
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            +
            2025-04-02 14:54:17,770 - INFO - Train Epoch: 20 [130/139 (94%)]	Loss: 2.0354	
         
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            +
            2025-04-02 14:54:23,545 - INFO - Epoch 20 - Train Loss: 2.0172
         
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| 389 | 
         
            +
            2025-04-02 14:54:47,509 - INFO - Epoch 20 - Validation Accuracy: 44.87%
         
     | 
| 390 | 
         
            +
            2025-04-02 14:54:47,509 - INFO - New best validation accuracy: 44.87%
         
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| 391 | 
         
            +
            2025-04-02 14:54:49,401 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/best_model
         
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            +
            2025-04-02 14:54:50,889 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
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| 393 | 
         
            +
            2025-04-02 14:55:14,711 - INFO - Final validation accuracy: 44.87%
         
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| 394 | 
         
            +
            2025-04-02 14:55:14,712 - INFO - Best validation accuracy: 44.87%
         
     | 
| 395 | 
         
            +
            2025-04-02 14:55:16,095 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_100_percent/checkpoints/checkpoint_last
         
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| 396 | 
         
            +
            2025-04-02 14:55:16,096 - INFO - Training completed
         
     | 
    	
        exp-rank-16/resnet/fewshot_10_percent/checkpoints/best_model/checkpoint.pth
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        exp-rank-16/resnet/fewshot_10_percent/checkpoints/best_model/lora_weights.safetensors
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        exp-rank-16/resnet/fewshot_10_percent/checkpoints/best_model/model.pth
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| 1 | 
         
            +
            2025-04-03 00:56:25,948 - INFO - Arguments: Namespace(datasets=['aml', 'fundus', 'mammo_calc', 'mammo_mass', 'pneumonia', 'oct', 'pbc', 'bloodmnist', 'breastmnist', 'octmnist', 'pneumoniamnist', 'retinamnist'], use_corruptions=False, severity_range=[1, 3], corruption_types=None, fewshot=0.1, epochs=20, batch_size=256, lr=0.0001, weight_decay=0.0001, temperature=2.0, alpha=0.5, backbone='resnet', lora_rank=16, lora_alpha=16, lora_dropout=0.1, device=device(type='cuda', index=6), gpu=6, seed=42, num_workers=4, output_dir='./outputs/exp2/resnet/fewshot_10_percent', log_interval=10, save_interval=1, eval_interval=1, resume=None)
         
     | 
| 2 | 
         
            +
            2025-04-03 00:56:25,948 - INFO - Creating dataloaders for datasets: ['aml', 'fundus', 'mammo_calc', 'mammo_mass', 'pneumonia', 'oct', 'pbc', 'bloodmnist', 'breastmnist', 'octmnist', 'pneumoniamnist', 'retinamnist']
         
     | 
| 3 | 
         
            +
            2025-04-03 00:56:56,699 - INFO - Initializing RobustMedClip model
         
     | 
| 4 | 
         
            +
            2025-04-03 00:57:05,774 - INFO - Starting training
         
     | 
| 5 | 
         
            +
            2025-04-03 00:57:05,774 - INFO - Epoch 1/20
         
     | 
| 6 | 
         
            +
            2025-04-03 00:57:07,750 - INFO - Train Epoch: 1 [0/14 (0%)]	Loss: 4.4771	
         
     | 
| 7 | 
         
            +
            2025-04-03 00:57:15,350 - INFO - Train Epoch: 1 [10/14 (71%)]	Loss: 4.3791	
         
     | 
| 8 | 
         
            +
            2025-04-03 00:57:17,604 - INFO - Epoch 1 - Train Loss: 4.4437
         
     | 
| 9 | 
         
            +
            2025-04-03 00:57:40,645 - INFO - Epoch 1 - Validation Accuracy: 3.66%
         
     | 
| 10 | 
         
            +
            2025-04-03 00:57:40,646 - INFO - New best validation accuracy: 3.66%
         
     | 
| 11 | 
         
            +
            2025-04-03 00:57:41,791 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/best_model
         
     | 
| 12 | 
         
            +
            2025-04-03 00:57:42,930 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 13 | 
         
            +
            2025-04-03 00:57:42,930 - INFO - Epoch 2/20
         
     | 
| 14 | 
         
            +
            2025-04-03 00:57:44,577 - INFO - Train Epoch: 2 [0/14 (0%)]	Loss: 4.3013	
         
     | 
| 15 | 
         
            +
            2025-04-03 00:57:52,221 - INFO - Train Epoch: 2 [10/14 (71%)]	Loss: 4.2776	
         
     | 
| 16 | 
         
            +
            2025-04-03 00:57:54,476 - INFO - Epoch 2 - Train Loss: 4.3320
         
     | 
| 17 | 
         
            +
            2025-04-03 00:58:17,398 - INFO - Epoch 2 - Validation Accuracy: 5.49%
         
     | 
| 18 | 
         
            +
            2025-04-03 00:58:17,398 - INFO - New best validation accuracy: 5.49%
         
     | 
| 19 | 
         
            +
            2025-04-03 00:58:18,781 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/best_model
         
     | 
| 20 | 
         
            +
            2025-04-03 00:58:20,008 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 21 | 
         
            +
            2025-04-03 00:58:20,008 - INFO - Epoch 3/20
         
     | 
| 22 | 
         
            +
            2025-04-03 00:58:21,721 - INFO - Train Epoch: 3 [0/14 (0%)]	Loss: 4.2289	
         
     | 
| 23 | 
         
            +
            2025-04-03 00:58:29,367 - INFO - Train Epoch: 3 [10/14 (71%)]	Loss: 4.0648	
         
     | 
| 24 | 
         
            +
            2025-04-03 00:58:31,584 - INFO - Epoch 3 - Train Loss: 4.1831
         
     | 
| 25 | 
         
            +
            2025-04-03 00:58:54,591 - INFO - Epoch 3 - Validation Accuracy: 5.31%
         
     | 
| 26 | 
         
            +
            2025-04-03 00:58:55,945 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 27 | 
         
            +
            2025-04-03 00:58:55,945 - INFO - Epoch 4/20
         
     | 
| 28 | 
         
            +
            2025-04-03 00:58:57,652 - INFO - Train Epoch: 4 [0/14 (0%)]	Loss: 4.1556	
         
     | 
| 29 | 
         
            +
            2025-04-03 00:59:05,399 - INFO - Train Epoch: 4 [10/14 (71%)]	Loss: 3.9845	
         
     | 
| 30 | 
         
            +
            2025-04-03 00:59:07,649 - INFO - Epoch 4 - Train Loss: 4.0466
         
     | 
| 31 | 
         
            +
            2025-04-03 00:59:30,511 - INFO - Epoch 4 - Validation Accuracy: 5.53%
         
     | 
| 32 | 
         
            +
            2025-04-03 00:59:30,511 - INFO - New best validation accuracy: 5.53%
         
     | 
| 33 | 
         
            +
            2025-04-03 00:59:31,814 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/best_model
         
     | 
| 34 | 
         
            +
            2025-04-03 00:59:33,102 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 35 | 
         
            +
            2025-04-03 00:59:33,102 - INFO - Epoch 5/20
         
     | 
| 36 | 
         
            +
            2025-04-03 00:59:34,865 - INFO - Train Epoch: 5 [0/14 (0%)]	Loss: 4.0378	
         
     | 
| 37 | 
         
            +
            2025-04-03 00:59:42,507 - INFO - Train Epoch: 5 [10/14 (71%)]	Loss: 3.9366	
         
     | 
| 38 | 
         
            +
            2025-04-03 00:59:44,740 - INFO - Epoch 5 - Train Loss: 3.9703
         
     | 
| 39 | 
         
            +
            2025-04-03 01:00:07,722 - INFO - Epoch 5 - Validation Accuracy: 5.82%
         
     | 
| 40 | 
         
            +
            2025-04-03 01:00:07,722 - INFO - New best validation accuracy: 5.82%
         
     | 
| 41 | 
         
            +
            2025-04-03 01:00:09,008 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/best_model
         
     | 
| 42 | 
         
            +
            2025-04-03 01:00:10,232 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 43 | 
         
            +
            2025-04-03 01:00:10,233 - INFO - Epoch 6/20
         
     | 
| 44 | 
         
            +
            2025-04-03 01:00:11,946 - INFO - Train Epoch: 6 [0/14 (0%)]	Loss: 4.0042	
         
     | 
| 45 | 
         
            +
            2025-04-03 01:00:19,637 - INFO - Train Epoch: 6 [10/14 (71%)]	Loss: 3.9399	
         
     | 
| 46 | 
         
            +
            2025-04-03 01:00:21,887 - INFO - Epoch 6 - Train Loss: 3.9133
         
     | 
| 47 | 
         
            +
            2025-04-03 01:00:44,608 - INFO - Epoch 6 - Validation Accuracy: 6.36%
         
     | 
| 48 | 
         
            +
            2025-04-03 01:00:44,608 - INFO - New best validation accuracy: 6.36%
         
     | 
| 49 | 
         
            +
            2025-04-03 01:00:46,988 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/best_model
         
     | 
| 50 | 
         
            +
            2025-04-03 01:00:48,269 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 51 | 
         
            +
            2025-04-03 01:00:48,269 - INFO - Epoch 7/20
         
     | 
| 52 | 
         
            +
            2025-04-03 01:00:49,983 - INFO - Train Epoch: 7 [0/14 (0%)]	Loss: 3.8369	
         
     | 
| 53 | 
         
            +
            2025-04-03 01:00:57,643 - INFO - Train Epoch: 7 [10/14 (71%)]	Loss: 3.8085	
         
     | 
| 54 | 
         
            +
            2025-04-03 01:00:59,893 - INFO - Epoch 7 - Train Loss: 3.8794
         
     | 
| 55 | 
         
            +
            2025-04-03 01:01:22,923 - INFO - Epoch 7 - Validation Accuracy: 7.20%
         
     | 
| 56 | 
         
            +
            2025-04-03 01:01:22,923 - INFO - New best validation accuracy: 7.20%
         
     | 
| 57 | 
         
            +
            2025-04-03 01:01:24,243 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/best_model
         
     | 
| 58 | 
         
            +
            2025-04-03 01:01:25,488 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 59 | 
         
            +
            2025-04-03 01:01:25,488 - INFO - Epoch 8/20
         
     | 
| 60 | 
         
            +
            2025-04-03 01:01:27,178 - INFO - Train Epoch: 8 [0/14 (0%)]	Loss: 3.9095	
         
     | 
| 61 | 
         
            +
            2025-04-03 01:01:34,823 - INFO - Train Epoch: 8 [10/14 (71%)]	Loss: 3.7926	
         
     | 
| 62 | 
         
            +
            2025-04-03 01:01:37,074 - INFO - Epoch 8 - Train Loss: 3.8377
         
     | 
| 63 | 
         
            +
            2025-04-03 01:01:59,945 - INFO - Epoch 8 - Validation Accuracy: 8.14%
         
     | 
| 64 | 
         
            +
            2025-04-03 01:01:59,946 - INFO - New best validation accuracy: 8.14%
         
     | 
| 65 | 
         
            +
            2025-04-03 01:02:01,291 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/best_model
         
     | 
| 66 | 
         
            +
            2025-04-03 01:02:02,491 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 67 | 
         
            +
            2025-04-03 01:02:02,491 - INFO - Epoch 9/20
         
     | 
| 68 | 
         
            +
            2025-04-03 01:02:04,195 - INFO - Train Epoch: 9 [0/14 (0%)]	Loss: 3.8417	
         
     | 
| 69 | 
         
            +
            2025-04-03 01:02:11,849 - INFO - Train Epoch: 9 [10/14 (71%)]	Loss: 3.8035	
         
     | 
| 70 | 
         
            +
            2025-04-03 01:02:14,093 - INFO - Epoch 9 - Train Loss: 3.7930
         
     | 
| 71 | 
         
            +
            2025-04-03 01:02:37,081 - INFO - Epoch 9 - Validation Accuracy: 8.77%
         
     | 
| 72 | 
         
            +
            2025-04-03 01:02:37,081 - INFO - New best validation accuracy: 8.77%
         
     | 
| 73 | 
         
            +
            2025-04-03 01:02:38,423 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/best_model
         
     | 
| 74 | 
         
            +
            2025-04-03 01:02:39,651 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 75 | 
         
            +
            2025-04-03 01:02:39,651 - INFO - Epoch 10/20
         
     | 
| 76 | 
         
            +
            2025-04-03 01:02:41,334 - INFO - Train Epoch: 10 [0/14 (0%)]	Loss: 3.7442	
         
     | 
| 77 | 
         
            +
            2025-04-03 01:02:48,997 - INFO - Train Epoch: 10 [10/14 (71%)]	Loss: 3.7480	
         
     | 
| 78 | 
         
            +
            2025-04-03 01:02:51,257 - INFO - Epoch 10 - Train Loss: 3.7501
         
     | 
| 79 | 
         
            +
            2025-04-03 01:03:14,202 - INFO - Epoch 10 - Validation Accuracy: 9.10%
         
     | 
| 80 | 
         
            +
            2025-04-03 01:03:14,202 - INFO - New best validation accuracy: 9.10%
         
     | 
| 81 | 
         
            +
            2025-04-03 01:03:15,499 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/best_model
         
     | 
| 82 | 
         
            +
            2025-04-03 01:03:16,753 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 83 | 
         
            +
            2025-04-03 01:03:16,754 - INFO - Epoch 11/20
         
     | 
| 84 | 
         
            +
            2025-04-03 01:03:18,414 - INFO - Train Epoch: 11 [0/14 (0%)]	Loss: 3.6758	
         
     | 
| 85 | 
         
            +
            2025-04-03 01:03:26,095 - INFO - Train Epoch: 11 [10/14 (71%)]	Loss: 3.6815	
         
     | 
| 86 | 
         
            +
            2025-04-03 01:03:28,342 - INFO - Epoch 11 - Train Loss: 3.6950
         
     | 
| 87 | 
         
            +
            2025-04-03 01:03:51,270 - INFO - Epoch 11 - Validation Accuracy: 9.61%
         
     | 
| 88 | 
         
            +
            2025-04-03 01:03:51,271 - INFO - New best validation accuracy: 9.61%
         
     | 
| 89 | 
         
            +
            2025-04-03 01:03:52,684 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/best_model
         
     | 
| 90 | 
         
            +
            2025-04-03 01:03:54,068 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 91 | 
         
            +
            2025-04-03 01:03:54,068 - INFO - Epoch 12/20
         
     | 
| 92 | 
         
            +
            2025-04-03 01:03:55,858 - INFO - Train Epoch: 12 [0/14 (0%)]	Loss: 3.6792	
         
     | 
| 93 | 
         
            +
            2025-04-03 01:04:03,513 - INFO - Train Epoch: 12 [10/14 (71%)]	Loss: 3.6223	
         
     | 
| 94 | 
         
            +
            2025-04-03 01:04:05,755 - INFO - Epoch 12 - Train Loss: 3.6420
         
     | 
| 95 | 
         
            +
            2025-04-03 01:04:28,644 - INFO - Epoch 12 - Validation Accuracy: 10.36%
         
     | 
| 96 | 
         
            +
            2025-04-03 01:04:28,644 - INFO - New best validation accuracy: 10.36%
         
     | 
| 97 | 
         
            +
            2025-04-03 01:04:29,918 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/best_model
         
     | 
| 98 | 
         
            +
            2025-04-03 01:04:31,320 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 99 | 
         
            +
            2025-04-03 01:04:31,320 - INFO - Epoch 13/20
         
     | 
| 100 | 
         
            +
            2025-04-03 01:04:33,100 - INFO - Train Epoch: 13 [0/14 (0%)]	Loss: 3.5838	
         
     | 
| 101 | 
         
            +
            2025-04-03 01:04:40,776 - INFO - Train Epoch: 13 [10/14 (71%)]	Loss: 3.5769	
         
     | 
| 102 | 
         
            +
            2025-04-03 01:04:43,051 - INFO - Epoch 13 - Train Loss: 3.5987
         
     | 
| 103 | 
         
            +
            2025-04-03 01:05:06,073 - INFO - Epoch 13 - Validation Accuracy: 11.44%
         
     | 
| 104 | 
         
            +
            2025-04-03 01:05:06,073 - INFO - New best validation accuracy: 11.44%
         
     | 
| 105 | 
         
            +
            2025-04-03 01:05:07,399 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/best_model
         
     | 
| 106 | 
         
            +
            2025-04-03 01:05:08,651 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 107 | 
         
            +
            2025-04-03 01:05:08,651 - INFO - Epoch 14/20
         
     | 
| 108 | 
         
            +
            2025-04-03 01:05:10,351 - INFO - Train Epoch: 14 [0/14 (0%)]	Loss: 3.5676	
         
     | 
| 109 | 
         
            +
            2025-04-03 01:05:18,019 - INFO - Train Epoch: 14 [10/14 (71%)]	Loss: 3.5488	
         
     | 
| 110 | 
         
            +
            2025-04-03 01:05:20,296 - INFO - Epoch 14 - Train Loss: 3.5675
         
     | 
| 111 | 
         
            +
            2025-04-03 01:05:43,004 - INFO - Epoch 14 - Validation Accuracy: 12.14%
         
     | 
| 112 | 
         
            +
            2025-04-03 01:05:43,005 - INFO - New best validation accuracy: 12.14%
         
     | 
| 113 | 
         
            +
            2025-04-03 01:05:44,331 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/best_model
         
     | 
| 114 | 
         
            +
            2025-04-03 01:05:45,671 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 115 | 
         
            +
            2025-04-03 01:05:45,671 - INFO - Epoch 15/20
         
     | 
| 116 | 
         
            +
            2025-04-03 01:05:47,391 - INFO - Train Epoch: 15 [0/14 (0%)]	Loss: 3.4755	
         
     | 
| 117 | 
         
            +
            2025-04-03 01:05:55,066 - INFO - Train Epoch: 15 [10/14 (71%)]	Loss: 3.5211	
         
     | 
| 118 | 
         
            +
            2025-04-03 01:05:57,292 - INFO - Epoch 15 - Train Loss: 3.5283
         
     | 
| 119 | 
         
            +
            2025-04-03 01:06:20,264 - INFO - Epoch 15 - Validation Accuracy: 12.11%
         
     | 
| 120 | 
         
            +
            2025-04-03 01:06:21,468 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 121 | 
         
            +
            2025-04-03 01:06:21,468 - INFO - Epoch 16/20
         
     | 
| 122 | 
         
            +
            2025-04-03 01:06:23,214 - INFO - Train Epoch: 16 [0/14 (0%)]	Loss: 3.4649	
         
     | 
| 123 | 
         
            +
            2025-04-03 01:06:30,858 - INFO - Train Epoch: 16 [10/14 (71%)]	Loss: 3.5502	
         
     | 
| 124 | 
         
            +
            2025-04-03 01:06:33,121 - INFO - Epoch 16 - Train Loss: 3.4946
         
     | 
| 125 | 
         
            +
            2025-04-03 01:06:55,923 - INFO - Epoch 16 - Validation Accuracy: 12.42%
         
     | 
| 126 | 
         
            +
            2025-04-03 01:06:55,923 - INFO - New best validation accuracy: 12.42%
         
     | 
| 127 | 
         
            +
            2025-04-03 01:06:57,290 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/best_model
         
     | 
| 128 | 
         
            +
            2025-04-03 01:06:58,541 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 129 | 
         
            +
            2025-04-03 01:06:58,541 - INFO - Epoch 17/20
         
     | 
| 130 | 
         
            +
            2025-04-03 01:07:00,224 - INFO - Train Epoch: 17 [0/14 (0%)]	Loss: 3.5104	
         
     | 
| 131 | 
         
            +
            2025-04-03 01:07:07,901 - INFO - Train Epoch: 17 [10/14 (71%)]	Loss: 3.4328	
         
     | 
| 132 | 
         
            +
            2025-04-03 01:07:10,149 - INFO - Epoch 17 - Train Loss: 3.4582
         
     | 
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            +
            2025-04-03 01:07:33,260 - INFO - Epoch 17 - Validation Accuracy: 14.26%
         
     | 
| 134 | 
         
            +
            2025-04-03 01:07:33,260 - INFO - New best validation accuracy: 14.26%
         
     | 
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            +
            2025-04-03 01:07:34,601 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/best_model
         
     | 
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            +
            2025-04-03 01:07:35,815 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 137 | 
         
            +
            2025-04-03 01:07:35,815 - INFO - Epoch 18/20
         
     | 
| 138 | 
         
            +
            2025-04-03 01:07:37,491 - INFO - Train Epoch: 18 [0/14 (0%)]	Loss: 3.6166	
         
     | 
| 139 | 
         
            +
            2025-04-03 01:07:45,136 - INFO - Train Epoch: 18 [10/14 (71%)]	Loss: 3.3389	
         
     | 
| 140 | 
         
            +
            2025-04-03 01:07:47,386 - INFO - Epoch 18 - Train Loss: 3.4320
         
     | 
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            +
            2025-04-03 01:08:10,252 - INFO - Epoch 18 - Validation Accuracy: 14.88%
         
     | 
| 142 | 
         
            +
            2025-04-03 01:08:10,252 - INFO - New best validation accuracy: 14.88%
         
     | 
| 143 | 
         
            +
            2025-04-03 01:08:11,692 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/best_model
         
     | 
| 144 | 
         
            +
            2025-04-03 01:08:12,918 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 145 | 
         
            +
            2025-04-03 01:08:12,918 - INFO - Epoch 19/20
         
     | 
| 146 | 
         
            +
            2025-04-03 01:08:14,609 - INFO - Train Epoch: 19 [0/14 (0%)]	Loss: 3.4113	
         
     | 
| 147 | 
         
            +
            2025-04-03 01:08:22,254 - INFO - Train Epoch: 19 [10/14 (71%)]	Loss: 3.3562	
         
     | 
| 148 | 
         
            +
            2025-04-03 01:08:24,498 - INFO - Epoch 19 - Train Loss: 3.4072
         
     | 
| 149 | 
         
            +
            2025-04-03 01:08:47,486 - INFO - Epoch 19 - Validation Accuracy: 16.43%
         
     | 
| 150 | 
         
            +
            2025-04-03 01:08:47,486 - INFO - New best validation accuracy: 16.43%
         
     | 
| 151 | 
         
            +
            2025-04-03 01:08:48,848 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/best_model
         
     | 
| 152 | 
         
            +
            2025-04-03 01:08:50,063 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 153 | 
         
            +
            2025-04-03 01:08:50,063 - INFO - Epoch 20/20
         
     | 
| 154 | 
         
            +
            2025-04-03 01:08:51,749 - INFO - Train Epoch: 20 [0/14 (0%)]	Loss: 3.2683	
         
     | 
| 155 | 
         
            +
            2025-04-03 01:08:59,398 - INFO - Train Epoch: 20 [10/14 (71%)]	Loss: 3.3672	
         
     | 
| 156 | 
         
            +
            2025-04-03 01:09:01,635 - INFO - Epoch 20 - Train Loss: 3.3749
         
     | 
| 157 | 
         
            +
            2025-04-03 01:09:25,044 - INFO - Epoch 20 - Validation Accuracy: 18.96%
         
     | 
| 158 | 
         
            +
            2025-04-03 01:09:25,044 - INFO - New best validation accuracy: 18.96%
         
     | 
| 159 | 
         
            +
            2025-04-03 01:09:26,404 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/best_model
         
     | 
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            +
            2025-04-03 01:09:27,751 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 161 | 
         
            +
            2025-04-03 01:09:50,801 - INFO - Final validation accuracy: 18.96%
         
     | 
| 162 | 
         
            +
            2025-04-03 01:09:50,801 - INFO - Best validation accuracy: 18.96%
         
     | 
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            +
            2025-04-03 01:09:51,991 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_10_percent/checkpoints/checkpoint_last
         
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| 164 | 
         
            +
            2025-04-03 01:09:51,991 - INFO - Training completed
         
     | 
    	
        exp-rank-16/resnet/fewshot_30_percent/checkpoints/best_model/checkpoint.pth
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        exp-rank-16/resnet/fewshot_30_percent/checkpoints/checkpoint_last/lora_weights.safetensors
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        exp-rank-16/resnet/fewshot_30_percent/checkpoints/checkpoint_last/model.pth
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| 1 | 
         
            +
            2025-04-03 01:10:01,371 - INFO - Arguments: Namespace(datasets=['aml', 'fundus', 'mammo_calc', 'mammo_mass', 'pneumonia', 'oct', 'pbc', 'bloodmnist', 'breastmnist', 'octmnist', 'pneumoniamnist', 'retinamnist'], use_corruptions=False, severity_range=[1, 3], corruption_types=None, fewshot=0.3, epochs=20, batch_size=256, lr=0.0001, weight_decay=0.0001, temperature=2.0, alpha=0.5, backbone='resnet', lora_rank=16, lora_alpha=16, lora_dropout=0.1, device=device(type='cuda', index=6), gpu=6, seed=42, num_workers=4, output_dir='./outputs/exp2/resnet/fewshot_30_percent', log_interval=10, save_interval=1, eval_interval=1, resume=None)
         
     | 
| 2 | 
         
            +
            2025-04-03 01:10:01,371 - INFO - Creating dataloaders for datasets: ['aml', 'fundus', 'mammo_calc', 'mammo_mass', 'pneumonia', 'oct', 'pbc', 'bloodmnist', 'breastmnist', 'octmnist', 'pneumoniamnist', 'retinamnist']
         
     | 
| 3 | 
         
            +
            2025-04-03 01:10:32,457 - INFO - Initializing RobustMedClip model
         
     | 
| 4 | 
         
            +
            2025-04-03 01:10:38,945 - INFO - Starting training
         
     | 
| 5 | 
         
            +
            2025-04-03 01:10:38,946 - INFO - Epoch 1/20
         
     | 
| 6 | 
         
            +
            2025-04-03 01:10:40,862 - INFO - Train Epoch: 1 [0/42 (0%)]	Loss: 4.5854	
         
     | 
| 7 | 
         
            +
            2025-04-03 01:10:48,402 - INFO - Train Epoch: 1 [10/42 (24%)]	Loss: 4.3735	
         
     | 
| 8 | 
         
            +
            2025-04-03 01:10:55,932 - INFO - Train Epoch: 1 [20/42 (48%)]	Loss: 4.2601	
         
     | 
| 9 | 
         
            +
            2025-04-03 01:11:03,569 - INFO - Train Epoch: 1 [30/42 (71%)]	Loss: 4.2088	
         
     | 
| 10 | 
         
            +
            2025-04-03 01:11:11,182 - INFO - Train Epoch: 1 [40/42 (95%)]	Loss: 4.2444	
         
     | 
| 11 | 
         
            +
            2025-04-03 01:11:11,607 - INFO - Epoch 1 - Train Loss: 4.3176
         
     | 
| 12 | 
         
            +
            2025-04-03 01:11:34,203 - INFO - Epoch 1 - Validation Accuracy: 5.26%
         
     | 
| 13 | 
         
            +
            2025-04-03 01:11:34,204 - INFO - New best validation accuracy: 5.26%
         
     | 
| 14 | 
         
            +
            2025-04-03 01:11:35,414 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/best_model
         
     | 
| 15 | 
         
            +
            2025-04-03 01:11:36,540 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
     | 
| 16 | 
         
            +
            2025-04-03 01:11:36,540 - INFO - Epoch 2/20
         
     | 
| 17 | 
         
            +
            2025-04-03 01:11:38,120 - INFO - Train Epoch: 2 [0/42 (0%)]	Loss: 4.1283	
         
     | 
| 18 | 
         
            +
            2025-04-03 01:11:45,805 - INFO - Train Epoch: 2 [10/42 (24%)]	Loss: 4.0279	
         
     | 
| 19 | 
         
            +
            2025-04-03 01:11:53,469 - INFO - Train Epoch: 2 [20/42 (48%)]	Loss: 3.9734	
         
     | 
| 20 | 
         
            +
            2025-04-03 01:12:01,138 - INFO - Train Epoch: 2 [30/42 (71%)]	Loss: 3.9627	
         
     | 
| 21 | 
         
            +
            2025-04-03 01:12:08,811 - INFO - Train Epoch: 2 [40/42 (95%)]	Loss: 3.8872	
         
     | 
| 22 | 
         
            +
            2025-04-03 01:12:09,243 - INFO - Epoch 2 - Train Loss: 3.9887
         
     | 
| 23 | 
         
            +
            2025-04-03 01:12:32,576 - INFO - Epoch 2 - Validation Accuracy: 6.88%
         
     | 
| 24 | 
         
            +
            2025-04-03 01:12:32,576 - INFO - New best validation accuracy: 6.88%
         
     | 
| 25 | 
         
            +
            2025-04-03 01:12:33,898 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/best_model
         
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            +
            2025-04-03 01:12:35,133 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
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| 27 | 
         
            +
            2025-04-03 01:12:35,133 - INFO - Epoch 3/20
         
     | 
| 28 | 
         
            +
            2025-04-03 01:12:36,824 - INFO - Train Epoch: 3 [0/42 (0%)]	Loss: 3.8934	
         
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| 29 | 
         
            +
            2025-04-03 01:12:44,441 - INFO - Train Epoch: 3 [10/42 (24%)]	Loss: 3.7839	
         
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| 30 | 
         
            +
            2025-04-03 01:12:52,069 - INFO - Train Epoch: 3 [20/42 (48%)]	Loss: 3.8145	
         
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| 31 | 
         
            +
            2025-04-03 01:12:59,693 - INFO - Train Epoch: 3 [30/42 (71%)]	Loss: 3.7579	
         
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| 32 | 
         
            +
            2025-04-03 01:13:07,337 - INFO - Train Epoch: 3 [40/42 (95%)]	Loss: 3.7666	
         
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| 33 | 
         
            +
            2025-04-03 01:13:07,752 - INFO - Epoch 3 - Train Loss: 3.8417
         
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| 34 | 
         
            +
            2025-04-03 01:13:30,187 - INFO - Epoch 3 - Validation Accuracy: 9.27%
         
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| 35 | 
         
            +
            2025-04-03 01:13:30,188 - INFO - New best validation accuracy: 9.27%
         
     | 
| 36 | 
         
            +
            2025-04-03 01:13:31,355 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/best_model
         
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            +
            2025-04-03 01:13:32,590 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
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| 38 | 
         
            +
            2025-04-03 01:13:32,590 - INFO - Epoch 4/20
         
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| 39 | 
         
            +
            2025-04-03 01:13:34,199 - INFO - Train Epoch: 4 [0/42 (0%)]	Loss: 3.8777	
         
     | 
| 40 | 
         
            +
            2025-04-03 01:13:41,817 - INFO - Train Epoch: 4 [10/42 (24%)]	Loss: 3.7311	
         
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| 41 | 
         
            +
            2025-04-03 01:13:49,438 - INFO - Train Epoch: 4 [20/42 (48%)]	Loss: 3.7443	
         
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| 42 | 
         
            +
            2025-04-03 01:13:57,081 - INFO - Train Epoch: 4 [30/42 (71%)]	Loss: 3.6386	
         
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| 43 | 
         
            +
            2025-04-03 01:14:04,710 - INFO - Train Epoch: 4 [40/42 (95%)]	Loss: 3.6008	
         
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| 44 | 
         
            +
            2025-04-03 01:14:05,122 - INFO - Epoch 4 - Train Loss: 3.6972
         
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| 45 | 
         
            +
            2025-04-03 01:14:27,345 - INFO - Epoch 4 - Validation Accuracy: 10.65%
         
     | 
| 46 | 
         
            +
            2025-04-03 01:14:27,346 - INFO - New best validation accuracy: 10.65%
         
     | 
| 47 | 
         
            +
            2025-04-03 01:14:28,633 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/best_model
         
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| 48 | 
         
            +
            2025-04-03 01:14:29,874 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
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| 49 | 
         
            +
            2025-04-03 01:14:29,874 - INFO - Epoch 5/20
         
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| 50 | 
         
            +
            2025-04-03 01:14:31,517 - INFO - Train Epoch: 5 [0/42 (0%)]	Loss: 3.5485	
         
     | 
| 51 | 
         
            +
            2025-04-03 01:14:39,149 - INFO - Train Epoch: 5 [10/42 (24%)]	Loss: 3.7418	
         
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| 52 | 
         
            +
            2025-04-03 01:14:46,765 - INFO - Train Epoch: 5 [20/42 (48%)]	Loss: 3.5738	
         
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| 53 | 
         
            +
            2025-04-03 01:14:54,387 - INFO - Train Epoch: 5 [30/42 (71%)]	Loss: 3.5214	
         
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| 54 | 
         
            +
            2025-04-03 01:15:02,011 - INFO - Train Epoch: 5 [40/42 (95%)]	Loss: 3.5233	
         
     | 
| 55 | 
         
            +
            2025-04-03 01:15:02,428 - INFO - Epoch 5 - Train Loss: 3.5759
         
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| 56 | 
         
            +
            2025-04-03 01:15:25,279 - INFO - Epoch 5 - Validation Accuracy: 12.11%
         
     | 
| 57 | 
         
            +
            2025-04-03 01:15:25,279 - INFO - New best validation accuracy: 12.11%
         
     | 
| 58 | 
         
            +
            2025-04-03 01:15:26,592 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/best_model
         
     | 
| 59 | 
         
            +
            2025-04-03 01:15:27,766 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
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| 60 | 
         
            +
            2025-04-03 01:15:27,766 - INFO - Epoch 6/20
         
     | 
| 61 | 
         
            +
            2025-04-03 01:15:29,432 - INFO - Train Epoch: 6 [0/42 (0%)]	Loss: 3.5468	
         
     | 
| 62 | 
         
            +
            2025-04-03 01:15:37,025 - INFO - Train Epoch: 6 [10/42 (24%)]	Loss: 3.4507	
         
     | 
| 63 | 
         
            +
            2025-04-03 01:15:44,646 - INFO - Train Epoch: 6 [20/42 (48%)]	Loss: 3.4291	
         
     | 
| 64 | 
         
            +
            2025-04-03 01:15:52,289 - INFO - Train Epoch: 6 [30/42 (71%)]	Loss: 3.4125	
         
     | 
| 65 | 
         
            +
            2025-04-03 01:15:59,926 - INFO - Train Epoch: 6 [40/42 (95%)]	Loss: 3.5163	
         
     | 
| 66 | 
         
            +
            2025-04-03 01:16:00,345 - INFO - Epoch 6 - Train Loss: 3.4742
         
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| 67 | 
         
            +
            2025-04-03 01:16:22,785 - INFO - Epoch 6 - Validation Accuracy: 13.54%
         
     | 
| 68 | 
         
            +
            2025-04-03 01:16:22,785 - INFO - New best validation accuracy: 13.54%
         
     | 
| 69 | 
         
            +
            2025-04-03 01:16:24,031 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/best_model
         
     | 
| 70 | 
         
            +
            2025-04-03 01:16:25,243 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
     | 
| 71 | 
         
            +
            2025-04-03 01:16:25,243 - INFO - Epoch 7/20
         
     | 
| 72 | 
         
            +
            2025-04-03 01:16:26,926 - INFO - Train Epoch: 7 [0/42 (0%)]	Loss: 3.4012	
         
     | 
| 73 | 
         
            +
            2025-04-03 01:16:34,542 - INFO - Train Epoch: 7 [10/42 (24%)]	Loss: 3.5195	
         
     | 
| 74 | 
         
            +
            2025-04-03 01:16:42,166 - INFO - Train Epoch: 7 [20/42 (48%)]	Loss: 3.4191	
         
     | 
| 75 | 
         
            +
            2025-04-03 01:16:49,777 - INFO - Train Epoch: 7 [30/42 (71%)]	Loss: 3.3120	
         
     | 
| 76 | 
         
            +
            2025-04-03 01:16:57,410 - INFO - Train Epoch: 7 [40/42 (95%)]	Loss: 3.3477	
         
     | 
| 77 | 
         
            +
            2025-04-03 01:16:57,828 - INFO - Epoch 7 - Train Loss: 3.3847
         
     | 
| 78 | 
         
            +
            2025-04-03 01:17:20,211 - INFO - Epoch 7 - Validation Accuracy: 17.74%
         
     | 
| 79 | 
         
            +
            2025-04-03 01:17:20,211 - INFO - New best validation accuracy: 17.74%
         
     | 
| 80 | 
         
            +
            2025-04-03 01:17:21,421 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/best_model
         
     | 
| 81 | 
         
            +
            2025-04-03 01:17:22,630 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
     | 
| 82 | 
         
            +
            2025-04-03 01:17:22,630 - INFO - Epoch 8/20
         
     | 
| 83 | 
         
            +
            2025-04-03 01:17:24,278 - INFO - Train Epoch: 8 [0/42 (0%)]	Loss: 3.3037	
         
     | 
| 84 | 
         
            +
            2025-04-03 01:17:31,906 - INFO - Train Epoch: 8 [10/42 (24%)]	Loss: 3.2954	
         
     | 
| 85 | 
         
            +
            2025-04-03 01:17:39,524 - INFO - Train Epoch: 8 [20/42 (48%)]	Loss: 3.2846	
         
     | 
| 86 | 
         
            +
            2025-04-03 01:17:47,130 - INFO - Train Epoch: 8 [30/42 (71%)]	Loss: 3.2343	
         
     | 
| 87 | 
         
            +
            2025-04-03 01:17:54,757 - INFO - Train Epoch: 8 [40/42 (95%)]	Loss: 3.2319	
         
     | 
| 88 | 
         
            +
            2025-04-03 01:17:55,180 - INFO - Epoch 8 - Train Loss: 3.2934
         
     | 
| 89 | 
         
            +
            2025-04-03 01:18:17,698 - INFO - Epoch 8 - Validation Accuracy: 23.76%
         
     | 
| 90 | 
         
            +
            2025-04-03 01:18:17,698 - INFO - New best validation accuracy: 23.76%
         
     | 
| 91 | 
         
            +
            2025-04-03 01:18:18,823 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/best_model
         
     | 
| 92 | 
         
            +
            2025-04-03 01:18:20,000 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
     | 
| 93 | 
         
            +
            2025-04-03 01:18:20,000 - INFO - Epoch 9/20
         
     | 
| 94 | 
         
            +
            2025-04-03 01:18:21,636 - INFO - Train Epoch: 9 [0/42 (0%)]	Loss: 3.3204	
         
     | 
| 95 | 
         
            +
            2025-04-03 01:18:29,254 - INFO - Train Epoch: 9 [10/42 (24%)]	Loss: 3.2838	
         
     | 
| 96 | 
         
            +
            2025-04-03 01:18:36,878 - INFO - Train Epoch: 9 [20/42 (48%)]	Loss: 3.1681	
         
     | 
| 97 | 
         
            +
            2025-04-03 01:18:44,512 - INFO - Train Epoch: 9 [30/42 (71%)]	Loss: 3.3006	
         
     | 
| 98 | 
         
            +
            2025-04-03 01:18:52,112 - INFO - Train Epoch: 9 [40/42 (95%)]	Loss: 3.1585	
         
     | 
| 99 | 
         
            +
            2025-04-03 01:18:52,523 - INFO - Epoch 9 - Train Loss: 3.1982
         
     | 
| 100 | 
         
            +
            2025-04-03 01:19:15,008 - INFO - Epoch 9 - Validation Accuracy: 20.92%
         
     | 
| 101 | 
         
            +
            2025-04-03 01:19:16,259 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
     | 
| 102 | 
         
            +
            2025-04-03 01:19:16,259 - INFO - Epoch 10/20
         
     | 
| 103 | 
         
            +
            2025-04-03 01:19:17,882 - INFO - Train Epoch: 10 [0/42 (0%)]	Loss: 3.1327	
         
     | 
| 104 | 
         
            +
            2025-04-03 01:19:25,498 - INFO - Train Epoch: 10 [10/42 (24%)]	Loss: 3.1187	
         
     | 
| 105 | 
         
            +
            2025-04-03 01:19:33,157 - INFO - Train Epoch: 10 [20/42 (48%)]	Loss: 3.1088	
         
     | 
| 106 | 
         
            +
            2025-04-03 01:19:40,807 - INFO - Train Epoch: 10 [30/42 (71%)]	Loss: 3.0296	
         
     | 
| 107 | 
         
            +
            2025-04-03 01:19:48,456 - INFO - Train Epoch: 10 [40/42 (95%)]	Loss: 3.0493	
         
     | 
| 108 | 
         
            +
            2025-04-03 01:19:48,876 - INFO - Epoch 10 - Train Loss: 3.1154
         
     | 
| 109 | 
         
            +
            2025-04-03 01:20:11,185 - INFO - Epoch 10 - Validation Accuracy: 29.06%
         
     | 
| 110 | 
         
            +
            2025-04-03 01:20:11,185 - INFO - New best validation accuracy: 29.06%
         
     | 
| 111 | 
         
            +
            2025-04-03 01:20:13,475 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/best_model
         
     | 
| 112 | 
         
            +
            2025-04-03 01:20:15,114 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
     | 
| 113 | 
         
            +
            2025-04-03 01:20:15,114 - INFO - Epoch 11/20
         
     | 
| 114 | 
         
            +
            2025-04-03 01:20:16,806 - INFO - Train Epoch: 11 [0/42 (0%)]	Loss: 3.0593	
         
     | 
| 115 | 
         
            +
            2025-04-03 01:20:24,450 - INFO - Train Epoch: 11 [10/42 (24%)]	Loss: 2.9980	
         
     | 
| 116 | 
         
            +
            2025-04-03 01:20:32,085 - INFO - Train Epoch: 11 [20/42 (48%)]	Loss: 3.0606	
         
     | 
| 117 | 
         
            +
            2025-04-03 01:20:39,721 - INFO - Train Epoch: 11 [30/42 (71%)]	Loss: 3.1429	
         
     | 
| 118 | 
         
            +
            2025-04-03 01:20:47,360 - INFO - Train Epoch: 11 [40/42 (95%)]	Loss: 2.9749	
         
     | 
| 119 | 
         
            +
            2025-04-03 01:20:47,774 - INFO - Epoch 11 - Train Loss: 3.0394
         
     | 
| 120 | 
         
            +
            2025-04-03 01:21:10,082 - INFO - Epoch 11 - Validation Accuracy: 29.52%
         
     | 
| 121 | 
         
            +
            2025-04-03 01:21:10,082 - INFO - New best validation accuracy: 29.52%
         
     | 
| 122 | 
         
            +
            2025-04-03 01:21:11,279 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/best_model
         
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| 123 | 
         
            +
            2025-04-03 01:21:12,510 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
     | 
| 124 | 
         
            +
            2025-04-03 01:21:12,510 - INFO - Epoch 12/20
         
     | 
| 125 | 
         
            +
            2025-04-03 01:21:14,171 - INFO - Train Epoch: 12 [0/42 (0%)]	Loss: 3.0459	
         
     | 
| 126 | 
         
            +
            2025-04-03 01:21:21,836 - INFO - Train Epoch: 12 [10/42 (24%)]	Loss: 2.9567	
         
     | 
| 127 | 
         
            +
            2025-04-03 01:21:29,504 - INFO - Train Epoch: 12 [20/42 (48%)]	Loss: 2.9509	
         
     | 
| 128 | 
         
            +
            2025-04-03 01:21:37,184 - INFO - Train Epoch: 12 [30/42 (71%)]	Loss: 2.8792	
         
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| 129 | 
         
            +
            2025-04-03 01:21:44,878 - INFO - Train Epoch: 12 [40/42 (95%)]	Loss: 2.9624	
         
     | 
| 130 | 
         
            +
            2025-04-03 01:21:45,305 - INFO - Epoch 12 - Train Loss: 2.9771
         
     | 
| 131 | 
         
            +
            2025-04-03 01:22:08,095 - INFO - Epoch 12 - Validation Accuracy: 28.67%
         
     | 
| 132 | 
         
            +
            2025-04-03 01:22:09,375 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
     | 
| 133 | 
         
            +
            2025-04-03 01:22:09,375 - INFO - Epoch 13/20
         
     | 
| 134 | 
         
            +
            2025-04-03 01:22:11,023 - INFO - Train Epoch: 13 [0/42 (0%)]	Loss: 2.8965	
         
     | 
| 135 | 
         
            +
            2025-04-03 01:22:18,661 - INFO - Train Epoch: 13 [10/42 (24%)]	Loss: 3.0182	
         
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| 136 | 
         
            +
            2025-04-03 01:22:26,289 - INFO - Train Epoch: 13 [20/42 (48%)]	Loss: 2.8722	
         
     | 
| 137 | 
         
            +
            2025-04-03 01:22:33,919 - INFO - Train Epoch: 13 [30/42 (71%)]	Loss: 2.9651	
         
     | 
| 138 | 
         
            +
            2025-04-03 01:22:41,509 - INFO - Train Epoch: 13 [40/42 (95%)]	Loss: 2.7654	
         
     | 
| 139 | 
         
            +
            2025-04-03 01:22:41,926 - INFO - Epoch 13 - Train Loss: 2.9228
         
     | 
| 140 | 
         
            +
            2025-04-03 01:23:04,348 - INFO - Epoch 13 - Validation Accuracy: 27.95%
         
     | 
| 141 | 
         
            +
            2025-04-03 01:23:05,604 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
     | 
| 142 | 
         
            +
            2025-04-03 01:23:05,604 - INFO - Epoch 14/20
         
     | 
| 143 | 
         
            +
            2025-04-03 01:23:07,273 - INFO - Train Epoch: 14 [0/42 (0%)]	Loss: 2.8823	
         
     | 
| 144 | 
         
            +
            2025-04-03 01:23:14,906 - INFO - Train Epoch: 14 [10/42 (24%)]	Loss: 3.0117	
         
     | 
| 145 | 
         
            +
            2025-04-03 01:23:22,529 - INFO - Train Epoch: 14 [20/42 (48%)]	Loss: 2.8088	
         
     | 
| 146 | 
         
            +
            2025-04-03 01:23:30,143 - INFO - Train Epoch: 14 [30/42 (71%)]	Loss: 2.7487	
         
     | 
| 147 | 
         
            +
            2025-04-03 01:23:37,759 - INFO - Train Epoch: 14 [40/42 (95%)]	Loss: 2.7790	
         
     | 
| 148 | 
         
            +
            2025-04-03 01:23:38,180 - INFO - Epoch 14 - Train Loss: 2.8661
         
     | 
| 149 | 
         
            +
            2025-04-03 01:24:00,479 - INFO - Epoch 14 - Validation Accuracy: 29.26%
         
     | 
| 150 | 
         
            +
            2025-04-03 01:24:01,672 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
     | 
| 151 | 
         
            +
            2025-04-03 01:24:01,673 - INFO - Epoch 15/20
         
     | 
| 152 | 
         
            +
            2025-04-03 01:24:03,322 - INFO - Train Epoch: 15 [0/42 (0%)]	Loss: 2.8640	
         
     | 
| 153 | 
         
            +
            2025-04-03 01:24:11,081 - INFO - Train Epoch: 15 [10/42 (24%)]	Loss: 2.8177	
         
     | 
| 154 | 
         
            +
            2025-04-03 01:24:18,733 - INFO - Train Epoch: 15 [20/42 (48%)]	Loss: 2.8138	
         
     | 
| 155 | 
         
            +
            2025-04-03 01:24:26,356 - INFO - Train Epoch: 15 [30/42 (71%)]	Loss: 2.7692	
         
     | 
| 156 | 
         
            +
            2025-04-03 01:24:33,993 - INFO - Train Epoch: 15 [40/42 (95%)]	Loss: 2.8406	
         
     | 
| 157 | 
         
            +
            2025-04-03 01:24:34,409 - INFO - Epoch 15 - Train Loss: 2.8136
         
     | 
| 158 | 
         
            +
            2025-04-03 01:24:56,938 - INFO - Epoch 15 - Validation Accuracy: 27.76%
         
     | 
| 159 | 
         
            +
            2025-04-03 01:24:58,184 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
     | 
| 160 | 
         
            +
            2025-04-03 01:24:58,184 - INFO - Epoch 16/20
         
     | 
| 161 | 
         
            +
            2025-04-03 01:24:59,819 - INFO - Train Epoch: 16 [0/42 (0%)]	Loss: 2.7583	
         
     | 
| 162 | 
         
            +
            2025-04-03 01:25:07,452 - INFO - Train Epoch: 16 [10/42 (24%)]	Loss: 2.8620	
         
     | 
| 163 | 
         
            +
            2025-04-03 01:25:15,057 - INFO - Train Epoch: 16 [20/42 (48%)]	Loss: 2.6715	
         
     | 
| 164 | 
         
            +
            2025-04-03 01:25:22,661 - INFO - Train Epoch: 16 [30/42 (71%)]	Loss: 2.7681	
         
     | 
| 165 | 
         
            +
            2025-04-03 01:25:30,273 - INFO - Train Epoch: 16 [40/42 (95%)]	Loss: 2.7212	
         
     | 
| 166 | 
         
            +
            2025-04-03 01:25:30,699 - INFO - Epoch 16 - Train Loss: 2.7621
         
     | 
| 167 | 
         
            +
            2025-04-03 01:25:52,957 - INFO - Epoch 16 - Validation Accuracy: 28.21%
         
     | 
| 168 | 
         
            +
            2025-04-03 01:25:54,175 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
     | 
| 169 | 
         
            +
            2025-04-03 01:25:54,175 - INFO - Epoch 17/20
         
     | 
| 170 | 
         
            +
            2025-04-03 01:25:55,823 - INFO - Train Epoch: 17 [0/42 (0%)]	Loss: 2.6676	
         
     | 
| 171 | 
         
            +
            2025-04-03 01:26:03,437 - INFO - Train Epoch: 17 [10/42 (24%)]	Loss: 2.6322	
         
     | 
| 172 | 
         
            +
            2025-04-03 01:26:11,050 - INFO - Train Epoch: 17 [20/42 (48%)]	Loss: 2.6923	
         
     | 
| 173 | 
         
            +
            2025-04-03 01:26:18,689 - INFO - Train Epoch: 17 [30/42 (71%)]	Loss: 2.7568	
         
     | 
| 174 | 
         
            +
            2025-04-03 01:26:26,328 - INFO - Train Epoch: 17 [40/42 (95%)]	Loss: 2.6752	
         
     | 
| 175 | 
         
            +
            2025-04-03 01:26:26,740 - INFO - Epoch 17 - Train Loss: 2.7106
         
     | 
| 176 | 
         
            +
            2025-04-03 01:26:49,563 - INFO - Epoch 17 - Validation Accuracy: 29.00%
         
     | 
| 177 | 
         
            +
            2025-04-03 01:26:50,787 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
     | 
| 178 | 
         
            +
            2025-04-03 01:26:50,787 - INFO - Epoch 18/20
         
     | 
| 179 | 
         
            +
            2025-04-03 01:26:52,453 - INFO - Train Epoch: 18 [0/42 (0%)]	Loss: 2.6312	
         
     | 
| 180 | 
         
            +
            2025-04-03 01:27:00,175 - INFO - Train Epoch: 18 [10/42 (24%)]	Loss: 2.6472	
         
     | 
| 181 | 
         
            +
            2025-04-03 01:27:07,894 - INFO - Train Epoch: 18 [20/42 (48%)]	Loss: 2.6186	
         
     | 
| 182 | 
         
            +
            2025-04-03 01:27:15,563 - INFO - Train Epoch: 18 [30/42 (71%)]	Loss: 2.6047	
         
     | 
| 183 | 
         
            +
            2025-04-03 01:27:23,165 - INFO - Train Epoch: 18 [40/42 (95%)]	Loss: 2.7139	
         
     | 
| 184 | 
         
            +
            2025-04-03 01:27:23,582 - INFO - Epoch 18 - Train Loss: 2.6784
         
     | 
| 185 | 
         
            +
            2025-04-03 01:27:45,976 - INFO - Epoch 18 - Validation Accuracy: 28.50%
         
     | 
| 186 | 
         
            +
            2025-04-03 01:27:47,145 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
     | 
| 187 | 
         
            +
            2025-04-03 01:27:47,146 - INFO - Epoch 19/20
         
     | 
| 188 | 
         
            +
            2025-04-03 01:27:48,763 - INFO - Train Epoch: 19 [0/42 (0%)]	Loss: 2.6626	
         
     | 
| 189 | 
         
            +
            2025-04-03 01:27:56,392 - INFO - Train Epoch: 19 [10/42 (24%)]	Loss: 2.7262	
         
     | 
| 190 | 
         
            +
            2025-04-03 01:28:04,036 - INFO - Train Epoch: 19 [20/42 (48%)]	Loss: 2.5900	
         
     | 
| 191 | 
         
            +
            2025-04-03 01:28:11,683 - INFO - Train Epoch: 19 [30/42 (71%)]	Loss: 2.5490	
         
     | 
| 192 | 
         
            +
            2025-04-03 01:28:19,363 - INFO - Train Epoch: 19 [40/42 (95%)]	Loss: 2.6195	
         
     | 
| 193 | 
         
            +
            2025-04-03 01:28:19,783 - INFO - Epoch 19 - Train Loss: 2.6453
         
     | 
| 194 | 
         
            +
            2025-04-03 01:28:42,858 - INFO - Epoch 19 - Validation Accuracy: 29.27%
         
     | 
| 195 | 
         
            +
            2025-04-03 01:28:44,172 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
     | 
| 196 | 
         
            +
            2025-04-03 01:28:44,172 - INFO - Epoch 20/20
         
     | 
| 197 | 
         
            +
            2025-04-03 01:28:45,828 - INFO - Train Epoch: 20 [0/42 (0%)]	Loss: 2.6073	
         
     | 
| 198 | 
         
            +
            2025-04-03 01:28:53,426 - INFO - Train Epoch: 20 [10/42 (24%)]	Loss: 2.7481	
         
     | 
| 199 | 
         
            +
            2025-04-03 01:29:01,060 - INFO - Train Epoch: 20 [20/42 (48%)]	Loss: 2.6463	
         
     | 
| 200 | 
         
            +
            2025-04-03 01:29:08,700 - INFO - Train Epoch: 20 [30/42 (71%)]	Loss: 2.6524	
         
     | 
| 201 | 
         
            +
            2025-04-03 01:29:16,342 - INFO - Train Epoch: 20 [40/42 (95%)]	Loss: 2.5949	
         
     | 
| 202 | 
         
            +
            2025-04-03 01:29:16,771 - INFO - Epoch 20 - Train Loss: 2.6154
         
     | 
| 203 | 
         
            +
            2025-04-03 01:29:39,144 - INFO - Epoch 20 - Validation Accuracy: 29.03%
         
     | 
| 204 | 
         
            +
            2025-04-03 01:29:40,345 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
     | 
| 205 | 
         
            +
            2025-04-03 01:30:02,784 - INFO - Final validation accuracy: 29.03%
         
     | 
| 206 | 
         
            +
            2025-04-03 01:30:02,784 - INFO - Best validation accuracy: 29.52%
         
     | 
| 207 | 
         
            +
            2025-04-03 01:30:03,950 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_30_percent/checkpoints/checkpoint_last
         
     | 
| 208 | 
         
            +
            2025-04-03 01:30:03,950 - INFO - Training completed
         
     | 
    	
        exp-rank-16/resnet/fewshot_75_percent/checkpoints/best_model/checkpoint.pth
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     | 
    	
        exp-rank-16/resnet/fewshot_75_percent/checkpoints/checkpoint_last/lora_weights.safetensors
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        exp-rank-16/resnet/fewshot_75_percent/checkpoints/checkpoint_last/model.pth
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| 1 | 
         
            +
            2025-04-03 01:30:13,044 - INFO - Arguments: Namespace(datasets=['aml', 'fundus', 'mammo_calc', 'mammo_mass', 'pneumonia', 'oct', 'pbc', 'bloodmnist', 'breastmnist', 'octmnist', 'pneumoniamnist', 'retinamnist'], use_corruptions=False, severity_range=[1, 3], corruption_types=None, fewshot=0.75, epochs=20, batch_size=256, lr=0.0001, weight_decay=0.0001, temperature=2.0, alpha=0.5, backbone='resnet', lora_rank=16, lora_alpha=16, lora_dropout=0.1, device=device(type='cuda', index=6), gpu=6, seed=42, num_workers=4, output_dir='./outputs/exp2/resnet/fewshot_75_percent', log_interval=10, save_interval=1, eval_interval=1, resume=None)
         
     | 
| 2 | 
         
            +
            2025-04-03 01:30:13,045 - INFO - Creating dataloaders for datasets: ['aml', 'fundus', 'mammo_calc', 'mammo_mass', 'pneumonia', 'oct', 'pbc', 'bloodmnist', 'breastmnist', 'octmnist', 'pneumoniamnist', 'retinamnist']
         
     | 
| 3 | 
         
            +
            2025-04-03 01:30:44,329 - INFO - Initializing RobustMedClip model
         
     | 
| 4 | 
         
            +
            2025-04-03 01:30:50,802 - INFO - Starting training
         
     | 
| 5 | 
         
            +
            2025-04-03 01:30:50,802 - INFO - Epoch 1/20
         
     | 
| 6 | 
         
            +
            2025-04-03 01:30:52,788 - INFO - Train Epoch: 1 [0/104 (0%)]	Loss: 4.4435	
         
     | 
| 7 | 
         
            +
            2025-04-03 01:31:00,472 - INFO - Train Epoch: 1 [10/104 (10%)]	Loss: 4.4472	
         
     | 
| 8 | 
         
            +
            2025-04-03 01:31:08,189 - INFO - Train Epoch: 1 [20/104 (19%)]	Loss: 4.3180	
         
     | 
| 9 | 
         
            +
            2025-04-03 01:31:15,913 - INFO - Train Epoch: 1 [30/104 (29%)]	Loss: 4.2816	
         
     | 
| 10 | 
         
            +
            2025-04-03 01:31:23,592 - INFO - Train Epoch: 1 [40/104 (38%)]	Loss: 4.1349	
         
     | 
| 11 | 
         
            +
            2025-04-03 01:31:31,300 - INFO - Train Epoch: 1 [50/104 (48%)]	Loss: 4.1235	
         
     | 
| 12 | 
         
            +
            2025-04-03 01:31:38,976 - INFO - Train Epoch: 1 [60/104 (58%)]	Loss: 3.9298	
         
     | 
| 13 | 
         
            +
            2025-04-03 01:31:46,666 - INFO - Train Epoch: 1 [70/104 (67%)]	Loss: 3.9198	
         
     | 
| 14 | 
         
            +
            2025-04-03 01:31:54,355 - INFO - Train Epoch: 1 [80/104 (77%)]	Loss: 3.8352	
         
     | 
| 15 | 
         
            +
            2025-04-03 01:32:02,062 - INFO - Train Epoch: 1 [90/104 (87%)]	Loss: 3.8732	
         
     | 
| 16 | 
         
            +
            2025-04-03 01:32:09,749 - INFO - Train Epoch: 1 [100/104 (96%)]	Loss: 3.9152	
         
     | 
| 17 | 
         
            +
            2025-04-03 01:32:11,886 - INFO - Epoch 1 - Train Loss: 4.1058
         
     | 
| 18 | 
         
            +
            2025-04-03 01:32:34,818 - INFO - Epoch 1 - Validation Accuracy: 8.55%
         
     | 
| 19 | 
         
            +
            2025-04-03 01:32:34,818 - INFO - New best validation accuracy: 8.55%
         
     | 
| 20 | 
         
            +
            2025-04-03 01:32:36,407 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/best_model
         
     | 
| 21 | 
         
            +
            2025-04-03 01:32:37,618 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
     | 
| 22 | 
         
            +
            2025-04-03 01:32:37,618 - INFO - Epoch 2/20
         
     | 
| 23 | 
         
            +
            2025-04-03 01:32:39,278 - INFO - Train Epoch: 2 [0/104 (0%)]	Loss: 3.8756	
         
     | 
| 24 | 
         
            +
            2025-04-03 01:32:46,983 - INFO - Train Epoch: 2 [10/104 (10%)]	Loss: 3.8692	
         
     | 
| 25 | 
         
            +
            2025-04-03 01:32:54,664 - INFO - Train Epoch: 2 [20/104 (19%)]	Loss: 3.7383	
         
     | 
| 26 | 
         
            +
            2025-04-03 01:33:02,423 - INFO - Train Epoch: 2 [30/104 (29%)]	Loss: 3.7109	
         
     | 
| 27 | 
         
            +
            2025-04-03 01:33:10,147 - INFO - Train Epoch: 2 [40/104 (38%)]	Loss: 3.7146	
         
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| 28 | 
         
            +
            2025-04-03 01:33:17,864 - INFO - Train Epoch: 2 [50/104 (48%)]	Loss: 3.6841	
         
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            +
            2025-04-03 01:33:25,559 - INFO - Train Epoch: 2 [60/104 (58%)]	Loss: 3.5990	
         
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            +
            2025-04-03 01:33:33,256 - INFO - Train Epoch: 2 [70/104 (67%)]	Loss: 3.6181	
         
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            +
            2025-04-03 01:33:40,945 - INFO - Train Epoch: 2 [80/104 (77%)]	Loss: 3.6002	
         
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            +
            2025-04-03 01:33:48,641 - INFO - Train Epoch: 2 [90/104 (87%)]	Loss: 3.5869	
         
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            +
            2025-04-03 01:33:56,350 - INFO - Train Epoch: 2 [100/104 (96%)]	Loss: 3.5065	
         
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| 34 | 
         
            +
            2025-04-03 01:33:58,459 - INFO - Epoch 2 - Train Loss: 3.6736
         
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| 35 | 
         
            +
            2025-04-03 01:34:21,412 - INFO - Epoch 2 - Validation Accuracy: 12.04%
         
     | 
| 36 | 
         
            +
            2025-04-03 01:34:21,412 - INFO - New best validation accuracy: 12.04%
         
     | 
| 37 | 
         
            +
            2025-04-03 01:34:23,194 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/best_model
         
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            +
            2025-04-03 01:34:24,454 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-03 01:34:24,454 - INFO - Epoch 3/20
         
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| 40 | 
         
            +
            2025-04-03 01:34:26,264 - INFO - Train Epoch: 3 [0/104 (0%)]	Loss: 3.5557	
         
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            +
            2025-04-03 01:34:33,926 - INFO - Train Epoch: 3 [10/104 (10%)]	Loss: 3.5258	
         
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            +
            2025-04-03 01:34:41,590 - INFO - Train Epoch: 3 [20/104 (19%)]	Loss: 3.4864	
         
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            +
            2025-04-03 01:34:49,323 - INFO - Train Epoch: 3 [30/104 (29%)]	Loss: 3.5381	
         
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            +
            2025-04-03 01:34:57,092 - INFO - Train Epoch: 3 [40/104 (38%)]	Loss: 3.4952	
         
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            +
            2025-04-03 01:35:04,809 - INFO - Train Epoch: 3 [50/104 (48%)]	Loss: 3.4272	
         
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            +
            2025-04-03 01:35:12,543 - INFO - Train Epoch: 3 [60/104 (58%)]	Loss: 3.4048	
         
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            +
            2025-04-03 01:35:20,228 - INFO - Train Epoch: 3 [70/104 (67%)]	Loss: 3.3689	
         
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            +
            2025-04-03 01:35:27,912 - INFO - Train Epoch: 3 [80/104 (77%)]	Loss: 3.3465	
         
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            +
            2025-04-03 01:35:35,594 - INFO - Train Epoch: 3 [90/104 (87%)]	Loss: 3.3744	
         
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            +
            2025-04-03 01:35:43,282 - INFO - Train Epoch: 3 [100/104 (96%)]	Loss: 3.2145	
         
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| 51 | 
         
            +
            2025-04-03 01:35:45,385 - INFO - Epoch 3 - Train Loss: 3.4161
         
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| 52 | 
         
            +
            2025-04-03 01:36:08,106 - INFO - Epoch 3 - Validation Accuracy: 21.06%
         
     | 
| 53 | 
         
            +
            2025-04-03 01:36:08,106 - INFO - New best validation accuracy: 21.06%
         
     | 
| 54 | 
         
            +
            2025-04-03 01:36:09,897 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/best_model
         
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| 55 | 
         
            +
            2025-04-03 01:36:11,908 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
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| 56 | 
         
            +
            2025-04-03 01:36:11,909 - INFO - Epoch 4/20
         
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| 57 | 
         
            +
            2025-04-03 01:36:13,586 - INFO - Train Epoch: 4 [0/104 (0%)]	Loss: 3.2246	
         
     | 
| 58 | 
         
            +
            2025-04-03 01:36:21,260 - INFO - Train Epoch: 4 [10/104 (10%)]	Loss: 3.2907	
         
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            +
            2025-04-03 01:36:28,946 - INFO - Train Epoch: 4 [20/104 (19%)]	Loss: 3.3580	
         
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            +
            2025-04-03 01:36:36,775 - INFO - Train Epoch: 4 [30/104 (29%)]	Loss: 3.2649	
         
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            +
            2025-04-03 01:36:44,521 - INFO - Train Epoch: 4 [40/104 (38%)]	Loss: 3.1972	
         
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            +
            2025-04-03 01:36:52,237 - INFO - Train Epoch: 4 [50/104 (48%)]	Loss: 3.2105	
         
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            +
            2025-04-03 01:36:59,994 - INFO - Train Epoch: 4 [60/104 (58%)]	Loss: 3.2121	
         
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| 64 | 
         
            +
            2025-04-03 01:37:07,685 - INFO - Train Epoch: 4 [70/104 (67%)]	Loss: 3.0754	
         
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| 65 | 
         
            +
            2025-04-03 01:37:15,380 - INFO - Train Epoch: 4 [80/104 (77%)]	Loss: 3.1332	
         
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| 66 | 
         
            +
            2025-04-03 01:37:23,058 - INFO - Train Epoch: 4 [90/104 (87%)]	Loss: 3.1055	
         
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| 67 | 
         
            +
            2025-04-03 01:37:30,773 - INFO - Train Epoch: 4 [100/104 (96%)]	Loss: 3.0453	
         
     | 
| 68 | 
         
            +
            2025-04-03 01:37:32,905 - INFO - Epoch 4 - Train Loss: 3.1930
         
     | 
| 69 | 
         
            +
            2025-04-03 01:37:55,581 - INFO - Epoch 4 - Validation Accuracy: 27.82%
         
     | 
| 70 | 
         
            +
            2025-04-03 01:37:55,581 - INFO - New best validation accuracy: 27.82%
         
     | 
| 71 | 
         
            +
            2025-04-03 01:37:57,343 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/best_model
         
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| 72 | 
         
            +
            2025-04-03 01:37:58,573 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
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| 73 | 
         
            +
            2025-04-03 01:37:58,574 - INFO - Epoch 5/20
         
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| 74 | 
         
            +
            2025-04-03 01:38:00,271 - INFO - Train Epoch: 5 [0/104 (0%)]	Loss: 3.0900	
         
     | 
| 75 | 
         
            +
            2025-04-03 01:38:08,015 - INFO - Train Epoch: 5 [10/104 (10%)]	Loss: 3.0084	
         
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            +
            2025-04-03 01:38:15,706 - INFO - Train Epoch: 5 [20/104 (19%)]	Loss: 3.0502	
         
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| 77 | 
         
            +
            2025-04-03 01:38:23,404 - INFO - Train Epoch: 5 [30/104 (29%)]	Loss: 2.9709	
         
     | 
| 78 | 
         
            +
            2025-04-03 01:38:31,073 - INFO - Train Epoch: 5 [40/104 (38%)]	Loss: 3.0550	
         
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| 79 | 
         
            +
            2025-04-03 01:38:38,772 - INFO - Train Epoch: 5 [50/104 (48%)]	Loss: 3.0306	
         
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| 80 | 
         
            +
            2025-04-03 01:38:46,472 - INFO - Train Epoch: 5 [60/104 (58%)]	Loss: 3.0669	
         
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| 81 | 
         
            +
            2025-04-03 01:38:54,222 - INFO - Train Epoch: 5 [70/104 (67%)]	Loss: 3.1172	
         
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| 82 | 
         
            +
            2025-04-03 01:39:01,925 - INFO - Train Epoch: 5 [80/104 (77%)]	Loss: 2.9203	
         
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| 83 | 
         
            +
            2025-04-03 01:39:09,616 - INFO - Train Epoch: 5 [90/104 (87%)]	Loss: 2.8900	
         
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| 84 | 
         
            +
            2025-04-03 01:39:17,293 - INFO - Train Epoch: 5 [100/104 (96%)]	Loss: 2.9681	
         
     | 
| 85 | 
         
            +
            2025-04-03 01:39:19,394 - INFO - Epoch 5 - Train Loss: 2.9974
         
     | 
| 86 | 
         
            +
            2025-04-03 01:39:41,993 - INFO - Epoch 5 - Validation Accuracy: 30.09%
         
     | 
| 87 | 
         
            +
            2025-04-03 01:39:41,994 - INFO - New best validation accuracy: 30.09%
         
     | 
| 88 | 
         
            +
            2025-04-03 01:39:43,680 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/best_model
         
     | 
| 89 | 
         
            +
            2025-04-03 01:39:44,924 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
     | 
| 90 | 
         
            +
            2025-04-03 01:39:44,924 - INFO - Epoch 6/20
         
     | 
| 91 | 
         
            +
            2025-04-03 01:39:46,599 - INFO - Train Epoch: 6 [0/104 (0%)]	Loss: 2.9372	
         
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| 92 | 
         
            +
            2025-04-03 01:39:54,278 - INFO - Train Epoch: 6 [10/104 (10%)]	Loss: 2.8977	
         
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            +
            2025-04-03 01:40:01,946 - INFO - Train Epoch: 6 [20/104 (19%)]	Loss: 2.9976	
         
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            +
            2025-04-03 01:40:09,679 - INFO - Train Epoch: 6 [30/104 (29%)]	Loss: 2.8925	
         
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| 95 | 
         
            +
            2025-04-03 01:40:17,454 - INFO - Train Epoch: 6 [40/104 (38%)]	Loss: 2.8012	
         
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| 96 | 
         
            +
            2025-04-03 01:40:25,130 - INFO - Train Epoch: 6 [50/104 (48%)]	Loss: 2.8586	
         
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            +
            2025-04-03 01:40:32,802 - INFO - Train Epoch: 6 [60/104 (58%)]	Loss: 2.8159	
         
     | 
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            +
            2025-04-03 01:40:40,545 - INFO - Train Epoch: 6 [70/104 (67%)]	Loss: 2.7961	
         
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            +
            2025-04-03 01:40:48,282 - INFO - Train Epoch: 6 [80/104 (77%)]	Loss: 2.7952	
         
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            +
            2025-04-03 01:40:56,066 - INFO - Train Epoch: 6 [90/104 (87%)]	Loss: 2.8781	
         
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            +
            2025-04-03 01:41:03,771 - INFO - Train Epoch: 6 [100/104 (96%)]	Loss: 2.7466	
         
     | 
| 102 | 
         
            +
            2025-04-03 01:41:05,884 - INFO - Epoch 6 - Train Loss: 2.8548
         
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| 103 | 
         
            +
            2025-04-03 01:41:28,684 - INFO - Epoch 6 - Validation Accuracy: 28.39%
         
     | 
| 104 | 
         
            +
            2025-04-03 01:41:30,781 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
     | 
| 105 | 
         
            +
            2025-04-03 01:41:30,782 - INFO - Epoch 7/20
         
     | 
| 106 | 
         
            +
            2025-04-03 01:41:32,486 - INFO - Train Epoch: 7 [0/104 (0%)]	Loss: 2.8413	
         
     | 
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            +
            2025-04-03 01:41:40,156 - INFO - Train Epoch: 7 [10/104 (10%)]	Loss: 2.7934	
         
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            +
            2025-04-03 01:41:47,822 - INFO - Train Epoch: 7 [20/104 (19%)]	Loss: 2.6438	
         
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| 109 | 
         
            +
            2025-04-03 01:41:55,486 - INFO - Train Epoch: 7 [30/104 (29%)]	Loss: 2.6843	
         
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            +
            2025-04-03 01:42:03,184 - INFO - Train Epoch: 7 [40/104 (38%)]	Loss: 2.8012	
         
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            +
            2025-04-03 01:42:10,864 - INFO - Train Epoch: 7 [50/104 (48%)]	Loss: 2.7166	
         
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            +
            2025-04-03 01:42:18,538 - INFO - Train Epoch: 7 [60/104 (58%)]	Loss: 2.6977	
         
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            +
            2025-04-03 01:42:26,204 - INFO - Train Epoch: 7 [70/104 (67%)]	Loss: 2.7297	
         
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| 114 | 
         
            +
            2025-04-03 01:42:33,876 - INFO - Train Epoch: 7 [80/104 (77%)]	Loss: 2.6165	
         
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| 115 | 
         
            +
            2025-04-03 01:42:41,551 - INFO - Train Epoch: 7 [90/104 (87%)]	Loss: 2.6980	
         
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| 116 | 
         
            +
            2025-04-03 01:42:49,241 - INFO - Train Epoch: 7 [100/104 (96%)]	Loss: 2.6096	
         
     | 
| 117 | 
         
            +
            2025-04-03 01:42:51,359 - INFO - Epoch 7 - Train Loss: 2.7299
         
     | 
| 118 | 
         
            +
            2025-04-03 01:43:14,132 - INFO - Epoch 7 - Validation Accuracy: 28.47%
         
     | 
| 119 | 
         
            +
            2025-04-03 01:43:15,416 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
     | 
| 120 | 
         
            +
            2025-04-03 01:43:15,416 - INFO - Epoch 8/20
         
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| 121 | 
         
            +
            2025-04-03 01:43:17,077 - INFO - Train Epoch: 8 [0/104 (0%)]	Loss: 2.6848	
         
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| 122 | 
         
            +
            2025-04-03 01:43:24,747 - INFO - Train Epoch: 8 [10/104 (10%)]	Loss: 2.6605	
         
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            +
            2025-04-03 01:43:32,423 - INFO - Train Epoch: 8 [20/104 (19%)]	Loss: 2.6695	
         
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| 124 | 
         
            +
            2025-04-03 01:43:40,103 - INFO - Train Epoch: 8 [30/104 (29%)]	Loss: 2.6677	
         
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| 125 | 
         
            +
            2025-04-03 01:43:47,770 - INFO - Train Epoch: 8 [40/104 (38%)]	Loss: 2.5701	
         
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| 126 | 
         
            +
            2025-04-03 01:43:55,456 - INFO - Train Epoch: 8 [50/104 (48%)]	Loss: 2.6838	
         
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| 127 | 
         
            +
            2025-04-03 01:44:03,190 - INFO - Train Epoch: 8 [60/104 (58%)]	Loss: 2.6700	
         
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| 128 | 
         
            +
            2025-04-03 01:44:10,874 - INFO - Train Epoch: 8 [70/104 (67%)]	Loss: 2.5827	
         
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| 129 | 
         
            +
            2025-04-03 01:44:18,555 - INFO - Train Epoch: 8 [80/104 (77%)]	Loss: 2.5898	
         
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            +
            2025-04-03 01:44:26,227 - INFO - Train Epoch: 8 [90/104 (87%)]	Loss: 2.6210	
         
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| 131 | 
         
            +
            2025-04-03 01:44:33,940 - INFO - Train Epoch: 8 [100/104 (96%)]	Loss: 2.6339	
         
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| 132 | 
         
            +
            2025-04-03 01:44:36,053 - INFO - Epoch 8 - Train Loss: 2.6448
         
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| 133 | 
         
            +
            2025-04-03 01:44:58,879 - INFO - Epoch 8 - Validation Accuracy: 29.73%
         
     | 
| 134 | 
         
            +
            2025-04-03 01:45:00,124 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
     | 
| 135 | 
         
            +
            2025-04-03 01:45:00,124 - INFO - Epoch 9/20
         
     | 
| 136 | 
         
            +
            2025-04-03 01:45:01,851 - INFO - Train Epoch: 9 [0/104 (0%)]	Loss: 2.5902	
         
     | 
| 137 | 
         
            +
            2025-04-03 01:45:09,599 - INFO - Train Epoch: 9 [10/104 (10%)]	Loss: 2.5626	
         
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| 138 | 
         
            +
            2025-04-03 01:45:17,281 - INFO - Train Epoch: 9 [20/104 (19%)]	Loss: 2.6072	
         
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            +
            2025-04-03 01:45:24,977 - INFO - Train Epoch: 9 [30/104 (29%)]	Loss: 2.5895	
         
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| 140 | 
         
            +
            2025-04-03 01:45:32,666 - INFO - Train Epoch: 9 [40/104 (38%)]	Loss: 2.5000	
         
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| 141 | 
         
            +
            2025-04-03 01:45:40,374 - INFO - Train Epoch: 9 [50/104 (48%)]	Loss: 2.7391	
         
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            +
            2025-04-03 01:45:48,066 - INFO - Train Epoch: 9 [60/104 (58%)]	Loss: 2.6057	
         
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            +
            2025-04-03 01:45:55,769 - INFO - Train Epoch: 9 [70/104 (67%)]	Loss: 2.5561	
         
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| 144 | 
         
            +
            2025-04-03 01:46:03,496 - INFO - Train Epoch: 9 [80/104 (77%)]	Loss: 2.6011	
         
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            +
            2025-04-03 01:46:11,185 - INFO - Train Epoch: 9 [90/104 (87%)]	Loss: 2.6279	
         
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| 146 | 
         
            +
            2025-04-03 01:46:18,854 - INFO - Train Epoch: 9 [100/104 (96%)]	Loss: 2.7456	
         
     | 
| 147 | 
         
            +
            2025-04-03 01:46:20,968 - INFO - Epoch 9 - Train Loss: 2.5792
         
     | 
| 148 | 
         
            +
            2025-04-03 01:46:43,872 - INFO - Epoch 9 - Validation Accuracy: 31.29%
         
     | 
| 149 | 
         
            +
            2025-04-03 01:46:43,872 - INFO - New best validation accuracy: 31.29%
         
     | 
| 150 | 
         
            +
            2025-04-03 01:46:45,701 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/best_model
         
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| 151 | 
         
            +
            2025-04-03 01:46:46,970 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
     | 
| 152 | 
         
            +
            2025-04-03 01:46:46,970 - INFO - Epoch 10/20
         
     | 
| 153 | 
         
            +
            2025-04-03 01:46:48,717 - INFO - Train Epoch: 10 [0/104 (0%)]	Loss: 2.4719	
         
     | 
| 154 | 
         
            +
            2025-04-03 01:46:56,420 - INFO - Train Epoch: 10 [10/104 (10%)]	Loss: 2.5787	
         
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            +
            2025-04-03 01:47:04,081 - INFO - Train Epoch: 10 [20/104 (19%)]	Loss: 2.4371	
         
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| 156 | 
         
            +
            2025-04-03 01:47:11,779 - INFO - Train Epoch: 10 [30/104 (29%)]	Loss: 2.5231	
         
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| 157 | 
         
            +
            2025-04-03 01:47:19,454 - INFO - Train Epoch: 10 [40/104 (38%)]	Loss: 2.5061	
         
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| 158 | 
         
            +
            2025-04-03 01:47:27,160 - INFO - Train Epoch: 10 [50/104 (48%)]	Loss: 2.4925	
         
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            +
            2025-04-03 01:47:34,839 - INFO - Train Epoch: 10 [60/104 (58%)]	Loss: 2.5309	
         
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            +
            2025-04-03 01:47:42,513 - INFO - Train Epoch: 10 [70/104 (67%)]	Loss: 2.5260	
         
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| 161 | 
         
            +
            2025-04-03 01:47:50,182 - INFO - Train Epoch: 10 [80/104 (77%)]	Loss: 2.4322	
         
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            +
            2025-04-03 01:47:57,912 - INFO - Train Epoch: 10 [90/104 (87%)]	Loss: 2.4387	
         
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| 163 | 
         
            +
            2025-04-03 01:48:05,644 - INFO - Train Epoch: 10 [100/104 (96%)]	Loss: 2.4094	
         
     | 
| 164 | 
         
            +
            2025-04-03 01:48:07,768 - INFO - Epoch 10 - Train Loss: 2.5240
         
     | 
| 165 | 
         
            +
            2025-04-03 01:48:30,580 - INFO - Epoch 10 - Validation Accuracy: 30.93%
         
     | 
| 166 | 
         
            +
            2025-04-03 01:48:31,929 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
     | 
| 167 | 
         
            +
            2025-04-03 01:48:31,930 - INFO - Epoch 11/20
         
     | 
| 168 | 
         
            +
            2025-04-03 01:48:33,608 - INFO - Train Epoch: 11 [0/104 (0%)]	Loss: 2.5692	
         
     | 
| 169 | 
         
            +
            2025-04-03 01:48:41,348 - INFO - Train Epoch: 11 [10/104 (10%)]	Loss: 2.4728	
         
     | 
| 170 | 
         
            +
            2025-04-03 01:48:49,080 - INFO - Train Epoch: 11 [20/104 (19%)]	Loss: 2.4597	
         
     | 
| 171 | 
         
            +
            2025-04-03 01:48:56,797 - INFO - Train Epoch: 11 [30/104 (29%)]	Loss: 2.5762	
         
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| 172 | 
         
            +
            2025-04-03 01:49:04,468 - INFO - Train Epoch: 11 [40/104 (38%)]	Loss: 2.4930	
         
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| 173 | 
         
            +
            2025-04-03 01:49:12,156 - INFO - Train Epoch: 11 [50/104 (48%)]	Loss: 2.5325	
         
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| 174 | 
         
            +
            2025-04-03 01:49:19,822 - INFO - Train Epoch: 11 [60/104 (58%)]	Loss: 2.4996	
         
     | 
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            +
            2025-04-03 01:49:27,489 - INFO - Train Epoch: 11 [70/104 (67%)]	Loss: 2.4077	
         
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            2025-04-03 01:49:50,508 - INFO - Train Epoch: 11 [100/104 (96%)]	Loss: 2.5312	
         
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            2025-04-03 01:49:52,615 - INFO - Epoch 11 - Train Loss: 2.4718
         
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            2025-04-03 01:50:15,501 - INFO - Epoch 11 - Validation Accuracy: 32.72%
         
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            2025-04-03 01:50:15,501 - INFO - New best validation accuracy: 32.72%
         
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            2025-04-03 01:50:17,245 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/best_model
         
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            2025-04-03 01:50:20,234 - INFO - Train Epoch: 12 [0/104 (0%)]	Loss: 2.5144	
         
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            2025-04-03 01:50:59,032 - INFO - Train Epoch: 12 [50/104 (48%)]	Loss: 2.4846	
         
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            2025-04-03 01:51:06,758 - INFO - Train Epoch: 12 [60/104 (58%)]	Loss: 2.4268	
         
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            2025-04-03 01:51:14,531 - INFO - Train Epoch: 12 [70/104 (67%)]	Loss: 2.4076	
         
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            2025-04-03 01:51:22,280 - INFO - Train Epoch: 12 [80/104 (77%)]	Loss: 2.3471	
         
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            2025-04-03 01:51:30,030 - INFO - Train Epoch: 12 [90/104 (87%)]	Loss: 2.3849	
         
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            2025-04-03 01:51:37,813 - INFO - Train Epoch: 12 [100/104 (96%)]	Loss: 2.3860	
         
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            2025-04-03 01:51:39,958 - INFO - Epoch 12 - Train Loss: 2.4124
         
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            2025-04-03 01:52:02,911 - INFO - Epoch 12 - Validation Accuracy: 31.50%
         
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            2025-04-03 01:52:04,326 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
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            2025-04-03 01:52:04,326 - INFO - Epoch 13/20
         
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            2025-04-03 01:52:06,046 - INFO - Train Epoch: 13 [0/104 (0%)]	Loss: 2.3783	
         
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            2025-04-03 01:52:13,700 - INFO - Train Epoch: 13 [10/104 (10%)]	Loss: 2.3805	
         
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            2025-04-03 01:52:21,383 - INFO - Train Epoch: 13 [20/104 (19%)]	Loss: 2.4060	
         
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            2025-04-03 01:52:36,759 - INFO - Train Epoch: 13 [40/104 (38%)]	Loss: 2.2339	
         
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            2025-04-03 01:52:44,462 - INFO - Train Epoch: 13 [50/104 (48%)]	Loss: 2.3760	
         
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            2025-04-03 01:52:52,174 - INFO - Train Epoch: 13 [60/104 (58%)]	Loss: 2.3151	
         
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            2025-04-03 01:52:59,838 - INFO - Train Epoch: 13 [70/104 (67%)]	Loss: 2.3144	
         
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            2025-04-03 01:53:07,524 - INFO - Train Epoch: 13 [80/104 (77%)]	Loss: 2.2688	
         
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            2025-04-03 01:53:15,195 - INFO - Train Epoch: 13 [90/104 (87%)]	Loss: 2.3977	
         
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            2025-04-03 01:53:22,864 - INFO - Train Epoch: 13 [100/104 (96%)]	Loss: 2.3075	
         
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            2025-04-03 01:53:24,975 - INFO - Epoch 13 - Train Loss: 2.3424
         
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            2025-04-03 01:53:47,753 - INFO - Epoch 13 - Validation Accuracy: 37.31%
         
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            +
            2025-04-03 01:53:47,753 - INFO - New best validation accuracy: 37.31%
         
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            +
            2025-04-03 01:53:49,564 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/best_model
         
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            2025-04-03 01:53:50,853 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
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            2025-04-03 01:53:50,854 - INFO - Epoch 14/20
         
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            2025-04-03 01:53:52,616 - INFO - Train Epoch: 14 [0/104 (0%)]	Loss: 2.3217	
         
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            2025-04-03 01:54:00,332 - INFO - Train Epoch: 14 [10/104 (10%)]	Loss: 2.2728	
         
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            2025-04-03 01:54:07,972 - INFO - Train Epoch: 14 [20/104 (19%)]	Loss: 2.2707	
         
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            2025-04-03 01:54:15,665 - INFO - Train Epoch: 14 [30/104 (29%)]	Loss: 2.2242	
         
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            2025-04-03 01:54:23,373 - INFO - Train Epoch: 14 [40/104 (38%)]	Loss: 2.2611	
         
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            2025-04-03 01:54:31,151 - INFO - Train Epoch: 14 [50/104 (48%)]	Loss: 2.3379	
         
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            2025-04-03 01:54:38,892 - INFO - Train Epoch: 14 [60/104 (58%)]	Loss: 2.2423	
         
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            2025-04-03 01:54:46,674 - INFO - Train Epoch: 14 [70/104 (67%)]	Loss: 2.2690	
         
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            2025-04-03 01:54:54,358 - INFO - Train Epoch: 14 [80/104 (77%)]	Loss: 2.3688	
         
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            2025-04-03 01:55:02,083 - INFO - Train Epoch: 14 [90/104 (87%)]	Loss: 2.2661	
         
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            2025-04-03 01:55:09,830 - INFO - Train Epoch: 14 [100/104 (96%)]	Loss: 2.2277	
         
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            2025-04-03 01:55:11,941 - INFO - Epoch 14 - Train Loss: 2.2844
         
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            +
            2025-04-03 01:55:34,740 - INFO - Epoch 14 - Validation Accuracy: 35.10%
         
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            +
            2025-04-03 01:55:36,053 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-03 01:55:36,053 - INFO - Epoch 15/20
         
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            2025-04-03 01:55:37,737 - INFO - Train Epoch: 15 [0/104 (0%)]	Loss: 2.2810	
         
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            2025-04-03 01:55:45,456 - INFO - Train Epoch: 15 [10/104 (10%)]	Loss: 2.3266	
         
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            2025-04-03 01:55:53,216 - INFO - Train Epoch: 15 [20/104 (19%)]	Loss: 2.3232	
         
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            2025-04-03 01:56:00,921 - INFO - Train Epoch: 15 [30/104 (29%)]	Loss: 2.2326	
         
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            2025-04-03 01:56:08,588 - INFO - Train Epoch: 15 [40/104 (38%)]	Loss: 2.3419	
         
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            2025-04-03 01:56:16,219 - INFO - Train Epoch: 15 [50/104 (48%)]	Loss: 2.1927	
         
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            2025-04-03 01:56:23,879 - INFO - Train Epoch: 15 [60/104 (58%)]	Loss: 2.2193	
         
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            2025-04-03 01:56:31,572 - INFO - Train Epoch: 15 [70/104 (67%)]	Loss: 2.1818	
         
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            2025-04-03 01:56:39,302 - INFO - Train Epoch: 15 [80/104 (77%)]	Loss: 2.1799	
         
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            2025-04-03 01:56:47,014 - INFO - Train Epoch: 15 [90/104 (87%)]	Loss: 2.2162	
         
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            2025-04-03 01:56:54,712 - INFO - Train Epoch: 15 [100/104 (96%)]	Loss: 2.1453	
         
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            +
            2025-04-03 01:56:56,842 - INFO - Epoch 15 - Train Loss: 2.2409
         
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            +
            2025-04-03 01:57:19,709 - INFO - Epoch 15 - Validation Accuracy: 36.55%
         
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            +
            2025-04-03 01:57:21,152 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-03 01:57:21,152 - INFO - Epoch 16/20
         
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            +
            2025-04-03 01:57:22,976 - INFO - Train Epoch: 16 [0/104 (0%)]	Loss: 2.2429	
         
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            +
            2025-04-03 01:57:30,650 - INFO - Train Epoch: 16 [10/104 (10%)]	Loss: 2.2603	
         
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            2025-04-03 01:57:38,324 - INFO - Train Epoch: 16 [20/104 (19%)]	Loss: 2.2286	
         
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            +
            2025-04-03 01:57:45,997 - INFO - Train Epoch: 16 [30/104 (29%)]	Loss: 2.1623	
         
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            +
            2025-04-03 01:57:53,669 - INFO - Train Epoch: 16 [40/104 (38%)]	Loss: 2.2630	
         
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            +
            2025-04-03 01:58:01,340 - INFO - Train Epoch: 16 [50/104 (48%)]	Loss: 2.1992	
         
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            2025-04-03 01:58:09,045 - INFO - Train Epoch: 16 [60/104 (58%)]	Loss: 2.2979	
         
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            +
            2025-04-03 01:58:16,730 - INFO - Train Epoch: 16 [70/104 (67%)]	Loss: 2.2393	
         
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            2025-04-03 01:58:24,414 - INFO - Train Epoch: 16 [80/104 (77%)]	Loss: 2.2049	
         
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            +
            2025-04-03 01:58:32,119 - INFO - Train Epoch: 16 [90/104 (87%)]	Loss: 2.1557	
         
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            +
            2025-04-03 01:58:39,792 - INFO - Train Epoch: 16 [100/104 (96%)]	Loss: 2.0796	
         
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            +
            2025-04-03 01:58:41,896 - INFO - Epoch 16 - Train Loss: 2.2155
         
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            +
            2025-04-03 01:59:04,543 - INFO - Epoch 16 - Validation Accuracy: 38.19%
         
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| 260 | 
         
            +
            2025-04-03 01:59:04,543 - INFO - New best validation accuracy: 38.19%
         
     | 
| 261 | 
         
            +
            2025-04-03 01:59:06,234 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/best_model
         
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            +
            2025-04-03 01:59:07,492 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-03 01:59:07,493 - INFO - Epoch 17/20
         
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| 264 | 
         
            +
            2025-04-03 01:59:09,203 - INFO - Train Epoch: 17 [0/104 (0%)]	Loss: 2.1706	
         
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            +
            2025-04-03 01:59:16,867 - INFO - Train Epoch: 17 [10/104 (10%)]	Loss: 2.1413	
         
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            +
            2025-04-03 01:59:24,538 - INFO - Train Epoch: 17 [20/104 (19%)]	Loss: 2.1481	
         
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            +
            2025-04-03 01:59:32,207 - INFO - Train Epoch: 17 [30/104 (29%)]	Loss: 2.2341	
         
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            +
            2025-04-03 01:59:39,882 - INFO - Train Epoch: 17 [40/104 (38%)]	Loss: 2.1319	
         
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            +
            2025-04-03 01:59:47,563 - INFO - Train Epoch: 17 [50/104 (48%)]	Loss: 2.0788	
         
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            +
            2025-04-03 01:59:55,235 - INFO - Train Epoch: 17 [60/104 (58%)]	Loss: 2.3008	
         
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            +
            2025-04-03 02:00:02,907 - INFO - Train Epoch: 17 [70/104 (67%)]	Loss: 2.0457	
         
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            +
            2025-04-03 02:00:10,587 - INFO - Train Epoch: 17 [80/104 (77%)]	Loss: 2.2078	
         
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            +
            2025-04-03 02:00:18,272 - INFO - Train Epoch: 17 [90/104 (87%)]	Loss: 2.2637	
         
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            +
            2025-04-03 02:00:25,975 - INFO - Train Epoch: 17 [100/104 (96%)]	Loss: 2.2741	
         
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            +
            2025-04-03 02:00:28,085 - INFO - Epoch 17 - Train Loss: 2.1837
         
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            +
            2025-04-03 02:00:50,940 - INFO - Epoch 17 - Validation Accuracy: 38.94%
         
     | 
| 277 | 
         
            +
            2025-04-03 02:00:50,940 - INFO - New best validation accuracy: 38.94%
         
     | 
| 278 | 
         
            +
            2025-04-03 02:00:52,576 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/best_model
         
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            +
            2025-04-03 02:00:53,805 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-03 02:00:53,805 - INFO - Epoch 18/20
         
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            +
            2025-04-03 02:00:55,503 - INFO - Train Epoch: 18 [0/104 (0%)]	Loss: 2.3479	
         
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            +
            2025-04-03 02:01:03,251 - INFO - Train Epoch: 18 [10/104 (10%)]	Loss: 2.1366	
         
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            +
            2025-04-03 02:01:10,971 - INFO - Train Epoch: 18 [20/104 (19%)]	Loss: 2.1164	
         
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            +
            2025-04-03 02:01:18,861 - INFO - Train Epoch: 18 [30/104 (29%)]	Loss: 2.1832	
         
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            +
            2025-04-03 02:01:26,687 - INFO - Train Epoch: 18 [40/104 (38%)]	Loss: 2.1303	
         
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            +
            2025-04-03 02:01:34,496 - INFO - Train Epoch: 18 [50/104 (48%)]	Loss: 2.1415	
         
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            +
            2025-04-03 02:01:42,226 - INFO - Train Epoch: 18 [60/104 (58%)]	Loss: 2.2047	
         
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            +
            2025-04-03 02:01:50,041 - INFO - Train Epoch: 18 [70/104 (67%)]	Loss: 2.1030	
         
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            +
            2025-04-03 02:01:57,793 - INFO - Train Epoch: 18 [80/104 (77%)]	Loss: 2.1796	
         
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            +
            2025-04-03 02:02:05,607 - INFO - Train Epoch: 18 [90/104 (87%)]	Loss: 2.0843	
         
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            +
            2025-04-03 02:02:13,370 - INFO - Train Epoch: 18 [100/104 (96%)]	Loss: 2.1812	
         
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| 292 | 
         
            +
            2025-04-03 02:02:15,509 - INFO - Epoch 18 - Train Loss: 2.1578
         
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| 293 | 
         
            +
            2025-04-03 02:02:38,473 - INFO - Epoch 18 - Validation Accuracy: 40.03%
         
     | 
| 294 | 
         
            +
            2025-04-03 02:02:38,473 - INFO - New best validation accuracy: 40.03%
         
     | 
| 295 | 
         
            +
            2025-04-03 02:02:40,206 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/best_model
         
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            +
            2025-04-03 02:02:41,493 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-03 02:02:41,493 - INFO - Epoch 19/20
         
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| 298 | 
         
            +
            2025-04-03 02:02:43,194 - INFO - Train Epoch: 19 [0/104 (0%)]	Loss: 2.1390	
         
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            +
            2025-04-03 02:02:50,961 - INFO - Train Epoch: 19 [10/104 (10%)]	Loss: 2.1024	
         
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            +
            2025-04-03 02:02:58,654 - INFO - Train Epoch: 19 [20/104 (19%)]	Loss: 2.2719	
         
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            +
            2025-04-03 02:03:06,386 - INFO - Train Epoch: 19 [30/104 (29%)]	Loss: 2.0415	
         
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            +
            2025-04-03 02:03:14,136 - INFO - Train Epoch: 19 [40/104 (38%)]	Loss: 2.1477	
         
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            +
            2025-04-03 02:03:21,882 - INFO - Train Epoch: 19 [50/104 (48%)]	Loss: 2.1322	
         
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            +
            2025-04-03 02:03:29,605 - INFO - Train Epoch: 19 [60/104 (58%)]	Loss: 2.1612	
         
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            +
            2025-04-03 02:03:37,304 - INFO - Train Epoch: 19 [70/104 (67%)]	Loss: 2.1194	
         
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            +
            2025-04-03 02:03:45,016 - INFO - Train Epoch: 19 [80/104 (77%)]	Loss: 2.0853	
         
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            +
            2025-04-03 02:03:52,732 - INFO - Train Epoch: 19 [90/104 (87%)]	Loss: 2.0269	
         
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            +
            2025-04-03 02:04:00,441 - INFO - Train Epoch: 19 [100/104 (96%)]	Loss: 2.2318	
         
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| 309 | 
         
            +
            2025-04-03 02:04:02,575 - INFO - Epoch 19 - Train Loss: 2.1319
         
     | 
| 310 | 
         
            +
            2025-04-03 02:04:25,381 - INFO - Epoch 19 - Validation Accuracy: 41.74%
         
     | 
| 311 | 
         
            +
            2025-04-03 02:04:25,381 - INFO - New best validation accuracy: 41.74%
         
     | 
| 312 | 
         
            +
            2025-04-03 02:04:27,100 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/best_model
         
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            +
            2025-04-03 02:04:28,311 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
     | 
| 314 | 
         
            +
            2025-04-03 02:04:28,312 - INFO - Epoch 20/20
         
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| 315 | 
         
            +
            2025-04-03 02:04:29,983 - INFO - Train Epoch: 20 [0/104 (0%)]	Loss: 2.1354	
         
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            +
            2025-04-03 02:04:37,745 - INFO - Train Epoch: 20 [10/104 (10%)]	Loss: 2.1539	
         
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            +
            2025-04-03 02:04:45,442 - INFO - Train Epoch: 20 [20/104 (19%)]	Loss: 2.0385	
         
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            +
            2025-04-03 02:04:53,178 - INFO - Train Epoch: 20 [30/104 (29%)]	Loss: 2.0575	
         
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            +
            2025-04-03 02:05:00,919 - INFO - Train Epoch: 20 [40/104 (38%)]	Loss: 2.1162	
         
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            +
            2025-04-03 02:05:08,711 - INFO - Train Epoch: 20 [50/104 (48%)]	Loss: 2.1226	
         
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            +
            2025-04-03 02:05:16,375 - INFO - Train Epoch: 20 [60/104 (58%)]	Loss: 2.1580	
         
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            +
            2025-04-03 02:05:24,094 - INFO - Train Epoch: 20 [70/104 (67%)]	Loss: 2.1330	
         
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            +
            2025-04-03 02:05:31,767 - INFO - Train Epoch: 20 [80/104 (77%)]	Loss: 2.0756	
         
     | 
| 324 | 
         
            +
            2025-04-03 02:05:39,540 - INFO - Train Epoch: 20 [90/104 (87%)]	Loss: 2.1556	
         
     | 
| 325 | 
         
            +
            2025-04-03 02:05:47,335 - INFO - Train Epoch: 20 [100/104 (96%)]	Loss: 2.1004	
         
     | 
| 326 | 
         
            +
            2025-04-03 02:05:49,468 - INFO - Epoch 20 - Train Loss: 2.1192
         
     | 
| 327 | 
         
            +
            2025-04-03 02:06:12,059 - INFO - Epoch 20 - Validation Accuracy: 40.38%
         
     | 
| 328 | 
         
            +
            2025-04-03 02:06:13,354 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
     | 
| 329 | 
         
            +
            2025-04-03 02:06:36,136 - INFO - Final validation accuracy: 40.38%
         
     | 
| 330 | 
         
            +
            2025-04-03 02:06:36,136 - INFO - Best validation accuracy: 41.74%
         
     | 
| 331 | 
         
            +
            2025-04-03 02:06:37,448 - INFO - Checkpoint saved to outputs/exp2/resnet/fewshot_75_percent/checkpoints/checkpoint_last
         
     | 
| 332 | 
         
            +
            2025-04-03 02:06:37,448 - INFO - Training completed
         
     | 
    	
        exp-rank-16/vit/fewshot_100_percent/checkpoints/best_model/checkpoint.pth
    ADDED
    
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| 1 | 
         
            +
            2025-04-03 03:18:35,196 - INFO - Arguments: Namespace(datasets=['aml', 'fundus', 'mammo_calc', 'mammo_mass', 'pneumonia', 'oct', 'pbc', 'bloodmnist', 'breastmnist', 'octmnist', 'pneumoniamnist', 'retinamnist'], use_corruptions=False, severity_range=[1, 3], corruption_types=None, fewshot=None, epochs=20, batch_size=256, lr=0.0001, weight_decay=0.0001, temperature=2.0, alpha=0.5, backbone='vit', lora_rank=16, lora_alpha=16, lora_dropout=0.1, device=device(type='cuda', index=5), gpu=5, seed=42, num_workers=4, output_dir='./outputs/exp2/vit/fewshot_100_percent', log_interval=10, save_interval=1, eval_interval=1, resume=None)
         
     | 
| 2 | 
         
            +
            2025-04-03 03:18:35,196 - INFO - Creating dataloaders for datasets: ['aml', 'fundus', 'mammo_calc', 'mammo_mass', 'pneumonia', 'oct', 'pbc', 'bloodmnist', 'breastmnist', 'octmnist', 'pneumoniamnist', 'retinamnist']
         
     | 
| 3 | 
         
            +
            2025-04-03 03:19:05,393 - INFO - Initializing RobustMedClip model
         
     | 
| 4 | 
         
            +
            2025-04-03 03:19:12,439 - INFO - Starting training
         
     | 
| 5 | 
         
            +
            2025-04-03 03:19:12,439 - INFO - Epoch 1/20
         
     | 
| 6 | 
         
            +
            2025-04-03 03:19:15,100 - INFO - Train Epoch: 1 [0/139 (0%)]	Loss: 5.8767	
         
     | 
| 7 | 
         
            +
            2025-04-03 03:19:31,948 - INFO - Train Epoch: 1 [10/139 (7%)]	Loss: 4.6353	
         
     | 
| 8 | 
         
            +
            2025-04-03 03:19:48,918 - INFO - Train Epoch: 1 [20/139 (14%)]	Loss: 3.8978	
         
     | 
| 9 | 
         
            +
            2025-04-03 03:20:05,973 - INFO - Train Epoch: 1 [30/139 (22%)]	Loss: 2.8041	
         
     | 
| 10 | 
         
            +
            2025-04-03 03:20:23,074 - INFO - Train Epoch: 1 [40/139 (29%)]	Loss: 2.4903	
         
     | 
| 11 | 
         
            +
            2025-04-03 03:20:40,223 - INFO - Train Epoch: 1 [50/139 (36%)]	Loss: 2.1117	
         
     | 
| 12 | 
         
            +
            2025-04-03 03:20:57,422 - INFO - Train Epoch: 1 [60/139 (43%)]	Loss: 1.8705	
         
     | 
| 13 | 
         
            +
            2025-04-03 03:21:14,621 - INFO - Train Epoch: 1 [70/139 (50%)]	Loss: 1.9268	
         
     | 
| 14 | 
         
            +
            2025-04-03 03:21:31,851 - INFO - Train Epoch: 1 [80/139 (58%)]	Loss: 1.6126	
         
     | 
| 15 | 
         
            +
            2025-04-03 03:21:49,083 - INFO - Train Epoch: 1 [90/139 (65%)]	Loss: 1.6640	
         
     | 
| 16 | 
         
            +
            2025-04-03 03:22:06,334 - INFO - Train Epoch: 1 [100/139 (72%)]	Loss: 1.6246	
         
     | 
| 17 | 
         
            +
            2025-04-03 03:22:23,581 - INFO - Train Epoch: 1 [110/139 (79%)]	Loss: 1.4682	
         
     | 
| 18 | 
         
            +
            2025-04-03 03:22:40,825 - INFO - Train Epoch: 1 [120/139 (86%)]	Loss: 1.3303	
         
     | 
| 19 | 
         
            +
            2025-04-03 03:22:58,073 - INFO - Train Epoch: 1 [130/139 (94%)]	Loss: 1.2319	
         
     | 
| 20 | 
         
            +
            2025-04-03 03:23:10,502 - INFO - Epoch 1 - Train Loss: 2.2803
         
     | 
| 21 | 
         
            +
            2025-04-03 03:23:56,079 - INFO - Epoch 1 - Validation Accuracy: 31.71%
         
     | 
| 22 | 
         
            +
            2025-04-03 03:23:56,080 - INFO - New best validation accuracy: 31.71%
         
     | 
| 23 | 
         
            +
            2025-04-03 03:23:58,035 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/best_model
         
     | 
| 24 | 
         
            +
            2025-04-03 03:23:59,570 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
     | 
| 25 | 
         
            +
            2025-04-03 03:23:59,570 - INFO - Epoch 2/20
         
     | 
| 26 | 
         
            +
            2025-04-03 03:24:02,301 - INFO - Train Epoch: 2 [0/139 (0%)]	Loss: 1.0871	
         
     | 
| 27 | 
         
            +
            2025-04-03 03:24:19,479 - INFO - Train Epoch: 2 [10/139 (7%)]	Loss: 1.0284	
         
     | 
| 28 | 
         
            +
            2025-04-03 03:24:36,713 - INFO - Train Epoch: 2 [20/139 (14%)]	Loss: 1.0864	
         
     | 
| 29 | 
         
            +
            2025-04-03 03:24:53,951 - INFO - Train Epoch: 2 [30/139 (22%)]	Loss: 1.0471	
         
     | 
| 30 | 
         
            +
            2025-04-03 03:25:11,223 - INFO - Train Epoch: 2 [40/139 (29%)]	Loss: 0.8571	
         
     | 
| 31 | 
         
            +
            2025-04-03 03:25:28,503 - INFO - Train Epoch: 2 [50/139 (36%)]	Loss: 0.9723	
         
     | 
| 32 | 
         
            +
            2025-04-03 03:25:45,776 - INFO - Train Epoch: 2 [60/139 (43%)]	Loss: 0.9472	
         
     | 
| 33 | 
         
            +
            2025-04-03 03:26:03,061 - INFO - Train Epoch: 2 [70/139 (50%)]	Loss: 0.8836	
         
     | 
| 34 | 
         
            +
            2025-04-03 03:26:20,339 - INFO - Train Epoch: 2 [80/139 (58%)]	Loss: 0.8380	
         
     | 
| 35 | 
         
            +
            2025-04-03 03:26:37,638 - INFO - Train Epoch: 2 [90/139 (65%)]	Loss: 0.8418	
         
     | 
| 36 | 
         
            +
            2025-04-03 03:26:54,917 - INFO - Train Epoch: 2 [100/139 (72%)]	Loss: 0.7141	
         
     | 
| 37 | 
         
            +
            2025-04-03 03:27:12,215 - INFO - Train Epoch: 2 [110/139 (79%)]	Loss: 0.7262	
         
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            +
            2025-04-03 03:27:29,495 - INFO - Train Epoch: 2 [120/139 (86%)]	Loss: 0.6968	
         
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            +
            2025-04-03 03:27:46,793 - INFO - Train Epoch: 2 [130/139 (94%)]	Loss: 0.7215	
         
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            +
            2025-04-03 03:27:59,276 - INFO - Epoch 2 - Train Loss: 0.9011
         
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            2025-04-03 03:28:44,756 - INFO - Epoch 2 - Validation Accuracy: 47.94%
         
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| 42 | 
         
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            2025-04-03 03:28:44,757 - INFO - New best validation accuracy: 47.94%
         
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            +
            2025-04-03 03:28:47,271 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/best_model
         
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            2025-04-03 03:28:49,009 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
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            2025-04-03 03:28:49,009 - INFO - Epoch 3/20
         
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            2025-04-03 03:28:51,591 - INFO - Train Epoch: 3 [0/139 (0%)]	Loss: 0.6718	
         
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            2025-04-03 03:29:08,733 - INFO - Train Epoch: 3 [10/139 (7%)]	Loss: 0.5652	
         
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            2025-04-03 03:29:25,916 - INFO - Train Epoch: 3 [20/139 (14%)]	Loss: 0.5986	
         
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            2025-04-03 03:29:43,118 - INFO - Train Epoch: 3 [30/139 (22%)]	Loss: 0.5277	
         
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            2025-04-03 03:30:00,326 - INFO - Train Epoch: 3 [40/139 (29%)]	Loss: 0.5429	
         
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            2025-04-03 03:30:17,538 - INFO - Train Epoch: 3 [50/139 (36%)]	Loss: 0.6189	
         
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            2025-04-03 03:30:34,760 - INFO - Train Epoch: 3 [60/139 (43%)]	Loss: 0.5689	
         
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            2025-04-03 03:30:51,982 - INFO - Train Epoch: 3 [70/139 (50%)]	Loss: 0.5455	
         
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            2025-04-03 03:31:09,210 - INFO - Train Epoch: 3 [80/139 (58%)]	Loss: 0.3994	
         
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            2025-04-03 03:31:26,449 - INFO - Train Epoch: 3 [90/139 (65%)]	Loss: 0.5070	
         
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            2025-04-03 03:31:43,690 - INFO - Train Epoch: 3 [100/139 (72%)]	Loss: 0.4325	
         
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            2025-04-03 03:32:00,939 - INFO - Train Epoch: 3 [110/139 (79%)]	Loss: 0.4641	
         
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            2025-04-03 03:32:18,179 - INFO - Train Epoch: 3 [120/139 (86%)]	Loss: 0.6050	
         
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            2025-04-03 03:32:35,439 - INFO - Train Epoch: 3 [130/139 (94%)]	Loss: 0.5805	
         
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            +
            2025-04-03 03:32:47,872 - INFO - Epoch 3 - Train Loss: 0.5706
         
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            +
            2025-04-03 03:33:33,242 - INFO - Epoch 3 - Validation Accuracy: 56.56%
         
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| 62 | 
         
            +
            2025-04-03 03:33:33,242 - INFO - New best validation accuracy: 56.56%
         
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| 63 | 
         
            +
            2025-04-03 03:33:35,770 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/best_model
         
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            +
            2025-04-03 03:33:37,410 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-03 03:33:37,410 - INFO - Epoch 4/20
         
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            +
            2025-04-03 03:33:40,033 - INFO - Train Epoch: 4 [0/139 (0%)]	Loss: 0.5116	
         
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            2025-04-03 03:33:57,165 - INFO - Train Epoch: 4 [10/139 (7%)]	Loss: 0.4393	
         
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            2025-04-03 03:34:14,336 - INFO - Train Epoch: 4 [20/139 (14%)]	Loss: 0.3933	
         
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            +
            2025-04-03 03:34:31,547 - INFO - Train Epoch: 4 [30/139 (22%)]	Loss: 0.4841	
         
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            2025-04-03 03:34:48,753 - INFO - Train Epoch: 4 [40/139 (29%)]	Loss: 0.5240	
         
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            2025-04-03 03:35:05,968 - INFO - Train Epoch: 4 [50/139 (36%)]	Loss: 0.5007	
         
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            2025-04-03 03:35:23,187 - INFO - Train Epoch: 4 [60/139 (43%)]	Loss: 0.4502	
         
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            +
            2025-04-03 03:35:40,410 - INFO - Train Epoch: 4 [70/139 (50%)]	Loss: 0.4657	
         
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            +
            2025-04-03 03:35:57,640 - INFO - Train Epoch: 4 [80/139 (58%)]	Loss: 0.3866	
         
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            +
            2025-04-03 03:36:14,867 - INFO - Train Epoch: 4 [90/139 (65%)]	Loss: 0.3480	
         
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            +
            2025-04-03 03:36:32,097 - INFO - Train Epoch: 4 [100/139 (72%)]	Loss: 0.3828	
         
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            +
            2025-04-03 03:36:49,328 - INFO - Train Epoch: 4 [110/139 (79%)]	Loss: 0.5205	
         
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            +
            2025-04-03 03:37:06,561 - INFO - Train Epoch: 4 [120/139 (86%)]	Loss: 0.4415	
         
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            +
            2025-04-03 03:37:23,797 - INFO - Train Epoch: 4 [130/139 (94%)]	Loss: 0.4608	
         
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            +
            2025-04-03 03:37:36,217 - INFO - Epoch 4 - Train Loss: 0.4333
         
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            +
            2025-04-03 03:38:21,596 - INFO - Epoch 4 - Validation Accuracy: 60.47%
         
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| 82 | 
         
            +
            2025-04-03 03:38:21,597 - INFO - New best validation accuracy: 60.47%
         
     | 
| 83 | 
         
            +
            2025-04-03 03:38:23,987 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/best_model
         
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            +
            2025-04-03 03:38:25,665 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-03 03:38:25,666 - INFO - Epoch 5/20
         
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            +
            2025-04-03 03:38:28,321 - INFO - Train Epoch: 5 [0/139 (0%)]	Loss: 0.4587	
         
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            +
            2025-04-03 03:38:45,479 - INFO - Train Epoch: 5 [10/139 (7%)]	Loss: 0.4666	
         
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            +
            2025-04-03 03:39:02,676 - INFO - Train Epoch: 5 [20/139 (14%)]	Loss: 0.3131	
         
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            +
            2025-04-03 03:39:19,892 - INFO - Train Epoch: 5 [30/139 (22%)]	Loss: 0.3434	
         
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            +
            2025-04-03 03:39:37,104 - INFO - Train Epoch: 5 [40/139 (29%)]	Loss: 0.4523	
         
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            +
            2025-04-03 03:39:54,328 - INFO - Train Epoch: 5 [50/139 (36%)]	Loss: 0.2825	
         
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            +
            2025-04-03 03:40:11,559 - INFO - Train Epoch: 5 [60/139 (43%)]	Loss: 0.3569	
         
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            +
            2025-04-03 03:40:28,798 - INFO - Train Epoch: 5 [70/139 (50%)]	Loss: 0.2694	
         
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            +
            2025-04-03 03:40:46,033 - INFO - Train Epoch: 5 [80/139 (58%)]	Loss: 0.3140	
         
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            +
            2025-04-03 03:41:03,268 - INFO - Train Epoch: 5 [90/139 (65%)]	Loss: 0.4332	
         
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            +
            2025-04-03 03:41:20,510 - INFO - Train Epoch: 5 [100/139 (72%)]	Loss: 0.3074	
         
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            +
            2025-04-03 03:41:37,755 - INFO - Train Epoch: 5 [110/139 (79%)]	Loss: 0.2648	
         
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            +
            2025-04-03 03:41:55,007 - INFO - Train Epoch: 5 [120/139 (86%)]	Loss: 0.3686	
         
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            +
            2025-04-03 03:42:12,252 - INFO - Train Epoch: 5 [130/139 (94%)]	Loss: 0.3267	
         
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            +
            2025-04-03 03:42:24,686 - INFO - Epoch 5 - Train Loss: 0.3611
         
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            +
            2025-04-03 03:43:10,055 - INFO - Epoch 5 - Validation Accuracy: 61.64%
         
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| 102 | 
         
            +
            2025-04-03 03:43:10,056 - INFO - New best validation accuracy: 61.64%
         
     | 
| 103 | 
         
            +
            2025-04-03 03:43:12,588 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/best_model
         
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            +
            2025-04-03 03:43:14,288 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-03 03:43:14,288 - INFO - Epoch 6/20
         
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            +
            2025-04-03 03:43:16,883 - INFO - Train Epoch: 6 [0/139 (0%)]	Loss: 0.3228	
         
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            +
            2025-04-03 03:43:34,051 - INFO - Train Epoch: 6 [10/139 (7%)]	Loss: 0.4016	
         
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            +
            2025-04-03 03:43:51,242 - INFO - Train Epoch: 6 [20/139 (14%)]	Loss: 0.3145	
         
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            +
            2025-04-03 03:44:08,458 - INFO - Train Epoch: 6 [30/139 (22%)]	Loss: 0.3793	
         
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            +
            2025-04-03 03:44:25,669 - INFO - Train Epoch: 6 [40/139 (29%)]	Loss: 0.3910	
         
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            +
            2025-04-03 03:44:42,881 - INFO - Train Epoch: 6 [50/139 (36%)]	Loss: 0.3195	
         
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            +
            2025-04-03 03:45:00,095 - INFO - Train Epoch: 6 [60/139 (43%)]	Loss: 0.3582	
         
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            +
            2025-04-03 03:45:17,323 - INFO - Train Epoch: 6 [70/139 (50%)]	Loss: 0.2837	
         
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            +
            2025-04-03 03:45:34,547 - INFO - Train Epoch: 6 [80/139 (58%)]	Loss: 0.3046	
         
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            +
            2025-04-03 03:45:51,777 - INFO - Train Epoch: 6 [90/139 (65%)]	Loss: 0.2599	
         
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            +
            2025-04-03 03:46:08,996 - INFO - Train Epoch: 6 [100/139 (72%)]	Loss: 0.2806	
         
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            +
            2025-04-03 03:46:26,223 - INFO - Train Epoch: 6 [110/139 (79%)]	Loss: 0.3017	
         
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            +
            2025-04-03 03:46:43,455 - INFO - Train Epoch: 6 [120/139 (86%)]	Loss: 0.2804	
         
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            +
            2025-04-03 03:47:00,708 - INFO - Train Epoch: 6 [130/139 (94%)]	Loss: 0.3804	
         
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| 120 | 
         
            +
            2025-04-03 03:47:13,153 - INFO - Epoch 6 - Train Loss: 0.3139
         
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| 121 | 
         
            +
            2025-04-03 03:47:58,619 - INFO - Epoch 6 - Validation Accuracy: 65.85%
         
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| 122 | 
         
            +
            2025-04-03 03:47:58,620 - INFO - New best validation accuracy: 65.85%
         
     | 
| 123 | 
         
            +
            2025-04-03 03:48:01,119 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/best_model
         
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            +
            2025-04-03 03:48:02,712 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-03 03:48:02,713 - INFO - Epoch 7/20
         
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| 126 | 
         
            +
            2025-04-03 03:48:05,316 - INFO - Train Epoch: 7 [0/139 (0%)]	Loss: 0.3005	
         
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            +
            2025-04-03 03:48:22,506 - INFO - Train Epoch: 7 [10/139 (7%)]	Loss: 0.3116	
         
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            +
            2025-04-03 03:48:39,690 - INFO - Train Epoch: 7 [20/139 (14%)]	Loss: 0.2720	
         
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            +
            2025-04-03 03:48:56,916 - INFO - Train Epoch: 7 [30/139 (22%)]	Loss: 0.3238	
         
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            +
            2025-04-03 03:49:14,132 - INFO - Train Epoch: 7 [40/139 (29%)]	Loss: 0.2959	
         
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            +
            2025-04-03 03:49:31,385 - INFO - Train Epoch: 7 [50/139 (36%)]	Loss: 0.2731	
         
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            +
            2025-04-03 03:49:48,637 - INFO - Train Epoch: 7 [60/139 (43%)]	Loss: 0.2286	
         
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            +
            2025-04-03 03:50:05,883 - INFO - Train Epoch: 7 [70/139 (50%)]	Loss: 0.2315	
         
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            +
            2025-04-03 03:50:23,136 - INFO - Train Epoch: 7 [80/139 (58%)]	Loss: 0.2146	
         
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            +
            2025-04-03 03:50:40,394 - INFO - Train Epoch: 7 [90/139 (65%)]	Loss: 0.2631	
         
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            +
            2025-04-03 03:50:57,647 - INFO - Train Epoch: 7 [100/139 (72%)]	Loss: 0.2277	
         
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            +
            2025-04-03 03:51:14,922 - INFO - Train Epoch: 7 [110/139 (79%)]	Loss: 0.2548	
         
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            +
            2025-04-03 03:51:32,183 - INFO - Train Epoch: 7 [120/139 (86%)]	Loss: 0.2491	
         
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            +
            2025-04-03 03:51:49,448 - INFO - Train Epoch: 7 [130/139 (94%)]	Loss: 0.2799	
         
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| 140 | 
         
            +
            2025-04-03 03:52:01,911 - INFO - Epoch 7 - Train Loss: 0.2851
         
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| 141 | 
         
            +
            2025-04-03 03:52:47,849 - INFO - Epoch 7 - Validation Accuracy: 67.91%
         
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| 142 | 
         
            +
            2025-04-03 03:52:47,849 - INFO - New best validation accuracy: 67.91%
         
     | 
| 143 | 
         
            +
            2025-04-03 03:52:50,330 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/best_model
         
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            +
            2025-04-03 03:52:52,130 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-03 03:52:52,130 - INFO - Epoch 8/20
         
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| 146 | 
         
            +
            2025-04-03 03:52:54,697 - INFO - Train Epoch: 8 [0/139 (0%)]	Loss: 0.2306	
         
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            +
            2025-04-03 03:53:11,831 - INFO - Train Epoch: 8 [10/139 (7%)]	Loss: 0.2622	
         
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            +
            2025-04-03 03:53:29,001 - INFO - Train Epoch: 8 [20/139 (14%)]	Loss: 0.3614	
         
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            +
            2025-04-03 03:53:46,207 - INFO - Train Epoch: 8 [30/139 (22%)]	Loss: 0.3005	
         
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            +
            2025-04-03 03:54:03,417 - INFO - Train Epoch: 8 [40/139 (29%)]	Loss: 0.2647	
         
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            +
            2025-04-03 03:54:20,623 - INFO - Train Epoch: 8 [50/139 (36%)]	Loss: 0.2225	
         
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            +
            2025-04-03 03:54:37,839 - INFO - Train Epoch: 8 [60/139 (43%)]	Loss: 0.3808	
         
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            +
            2025-04-03 03:54:55,063 - INFO - Train Epoch: 8 [70/139 (50%)]	Loss: 0.2648	
         
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            +
            2025-04-03 03:55:12,293 - INFO - Train Epoch: 8 [80/139 (58%)]	Loss: 0.2883	
         
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            +
            2025-04-03 03:55:29,536 - INFO - Train Epoch: 8 [90/139 (65%)]	Loss: 0.2767	
         
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            +
            2025-04-03 03:55:46,765 - INFO - Train Epoch: 8 [100/139 (72%)]	Loss: 0.2244	
         
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            +
            2025-04-03 03:56:04,004 - INFO - Train Epoch: 8 [110/139 (79%)]	Loss: 0.2068	
         
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            +
            2025-04-03 03:56:21,246 - INFO - Train Epoch: 8 [120/139 (86%)]	Loss: 0.2332	
         
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            +
            2025-04-03 03:56:38,498 - INFO - Train Epoch: 8 [130/139 (94%)]	Loss: 0.2448	
         
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| 160 | 
         
            +
            2025-04-03 03:56:50,928 - INFO - Epoch 8 - Train Loss: 0.2601
         
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| 161 | 
         
            +
            2025-04-03 03:57:36,227 - INFO - Epoch 8 - Validation Accuracy: 71.27%
         
     | 
| 162 | 
         
            +
            2025-04-03 03:57:36,227 - INFO - New best validation accuracy: 71.27%
         
     | 
| 163 | 
         
            +
            2025-04-03 03:57:38,740 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/best_model
         
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            +
            2025-04-03 03:57:40,344 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-03 03:57:40,344 - INFO - Epoch 9/20
         
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            +
            2025-04-03 03:57:42,880 - INFO - Train Epoch: 9 [0/139 (0%)]	Loss: 0.2574	
         
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            +
            2025-04-03 03:58:00,010 - INFO - Train Epoch: 9 [10/139 (7%)]	Loss: 0.3646	
         
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            +
            2025-04-03 03:58:17,224 - INFO - Train Epoch: 9 [20/139 (14%)]	Loss: 0.2166	
         
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            +
            2025-04-03 03:58:34,448 - INFO - Train Epoch: 9 [30/139 (22%)]	Loss: 0.2814	
         
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            +
            2025-04-03 03:58:51,655 - INFO - Train Epoch: 9 [40/139 (29%)]	Loss: 0.2854	
         
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            +
            2025-04-03 03:59:08,866 - INFO - Train Epoch: 9 [50/139 (36%)]	Loss: 0.2795	
         
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            +
            2025-04-03 03:59:26,078 - INFO - Train Epoch: 9 [60/139 (43%)]	Loss: 0.1893	
         
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            +
            2025-04-03 03:59:43,286 - INFO - Train Epoch: 9 [70/139 (50%)]	Loss: 0.2925	
         
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            +
            2025-04-03 04:00:00,509 - INFO - Train Epoch: 9 [80/139 (58%)]	Loss: 0.2155	
         
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            +
            2025-04-03 04:00:17,729 - INFO - Train Epoch: 9 [90/139 (65%)]	Loss: 0.1658	
         
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            +
            2025-04-03 04:00:34,964 - INFO - Train Epoch: 9 [100/139 (72%)]	Loss: 0.2003	
         
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            +
            2025-04-03 04:00:52,194 - INFO - Train Epoch: 9 [110/139 (79%)]	Loss: 0.2587	
         
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            +
            2025-04-03 04:01:09,433 - INFO - Train Epoch: 9 [120/139 (86%)]	Loss: 0.2920	
         
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            +
            2025-04-03 04:01:26,697 - INFO - Train Epoch: 9 [130/139 (94%)]	Loss: 0.2020	
         
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| 180 | 
         
            +
            2025-04-03 04:01:39,128 - INFO - Epoch 9 - Train Loss: 0.2452
         
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| 181 | 
         
            +
            2025-04-03 04:02:24,637 - INFO - Epoch 9 - Validation Accuracy: 69.91%
         
     | 
| 182 | 
         
            +
            2025-04-03 04:02:26,315 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
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| 183 | 
         
            +
            2025-04-03 04:02:26,315 - INFO - Epoch 10/20
         
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| 184 | 
         
            +
            2025-04-03 04:02:28,862 - INFO - Train Epoch: 10 [0/139 (0%)]	Loss: 0.2645	
         
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            2025-04-03 04:07:11,939 - INFO - Epoch 10 - Validation Accuracy: 71.34%
         
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            2025-04-03 04:07:11,939 - INFO - New best validation accuracy: 71.34%
         
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            2025-04-03 04:11:14,886 - INFO - Epoch 11 - Train Loss: 0.2111
         
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            2025-04-03 04:12:00,490 - INFO - Epoch 11 - Validation Accuracy: 73.77%
         
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            2025-04-03 04:12:00,490 - INFO - New best validation accuracy: 73.77%
         
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            2025-04-03 04:12:03,047 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/best_model
         
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            2025-04-03 04:12:04,739 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
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            2025-04-03 04:12:04,739 - INFO - Epoch 12/20
         
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            2025-04-03 04:12:07,380 - INFO - Train Epoch: 12 [0/139 (0%)]	Loss: 0.1640	
         
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            2025-04-03 04:12:24,524 - INFO - Train Epoch: 12 [10/139 (7%)]	Loss: 0.1995	
         
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            2025-04-03 04:15:33,912 - INFO - Train Epoch: 12 [120/139 (86%)]	Loss: 0.1815	
         
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            2025-04-03 04:16:03,558 - INFO - Epoch 12 - Train Loss: 0.2040
         
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            2025-04-03 04:16:48,591 - INFO - Epoch 12 - Validation Accuracy: 75.49%
         
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            2025-04-03 04:16:48,591 - INFO - New best validation accuracy: 75.49%
         
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            2025-04-03 04:16:50,987 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/best_model
         
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            2025-04-03 04:16:52,721 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
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            2025-04-03 04:16:52,721 - INFO - Epoch 13/20
         
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            2025-04-03 04:16:55,311 - INFO - Train Epoch: 13 [0/139 (0%)]	Loss: 0.1150	
         
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            2025-04-03 04:17:12,460 - INFO - Train Epoch: 13 [10/139 (7%)]	Loss: 0.2928	
         
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            2025-04-03 04:18:38,566 - INFO - Train Epoch: 13 [60/139 (43%)]	Loss: 0.2340	
         
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            2025-04-03 04:18:55,808 - INFO - Train Epoch: 13 [70/139 (50%)]	Loss: 0.2325	
         
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            2025-04-03 04:19:30,347 - INFO - Train Epoch: 13 [90/139 (65%)]	Loss: 0.2033	
         
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            2025-04-03 04:19:47,612 - INFO - Train Epoch: 13 [100/139 (72%)]	Loss: 0.2368	
         
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            2025-04-03 04:20:04,871 - INFO - Train Epoch: 13 [110/139 (79%)]	Loss: 0.2086	
         
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            2025-04-03 04:20:22,134 - INFO - Train Epoch: 13 [120/139 (86%)]	Loss: 0.2314	
         
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            2025-04-03 04:20:39,393 - INFO - Train Epoch: 13 [130/139 (94%)]	Loss: 0.1996	
         
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            2025-04-03 04:20:51,839 - INFO - Epoch 13 - Train Loss: 0.1937
         
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            2025-04-03 04:21:37,289 - INFO - Epoch 13 - Validation Accuracy: 76.45%
         
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            +
            2025-04-03 04:21:37,289 - INFO - New best validation accuracy: 76.45%
         
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            +
            2025-04-03 04:21:39,724 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/best_model
         
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            2025-04-03 04:21:41,406 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
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            2025-04-03 04:21:41,406 - INFO - Epoch 14/20
         
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            2025-04-03 04:21:43,995 - INFO - Train Epoch: 14 [0/139 (0%)]	Loss: 0.1591	
         
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            2025-04-03 04:22:01,159 - INFO - Train Epoch: 14 [10/139 (7%)]	Loss: 0.1571	
         
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            2025-04-03 04:22:18,359 - INFO - Train Epoch: 14 [20/139 (14%)]	Loss: 0.2044	
         
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            2025-04-03 04:22:35,555 - INFO - Train Epoch: 14 [30/139 (22%)]	Loss: 0.2031	
         
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            2025-04-03 04:23:27,240 - INFO - Train Epoch: 14 [60/139 (43%)]	Loss: 0.1851	
         
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            2025-04-03 04:24:18,960 - INFO - Train Epoch: 14 [90/139 (65%)]	Loss: 0.1480	
         
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            2025-04-03 04:24:36,206 - INFO - Train Epoch: 14 [100/139 (72%)]	Loss: 0.1652	
         
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            2025-04-03 04:24:53,446 - INFO - Train Epoch: 14 [110/139 (79%)]	Loss: 0.1906	
         
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            2025-04-03 04:25:10,686 - INFO - Train Epoch: 14 [120/139 (86%)]	Loss: 0.1689	
         
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            2025-04-03 04:25:27,933 - INFO - Train Epoch: 14 [130/139 (94%)]	Loss: 0.1773	
         
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            2025-04-03 04:25:40,389 - INFO - Epoch 14 - Train Loss: 0.1922
         
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            2025-04-03 04:26:25,817 - INFO - Epoch 14 - Validation Accuracy: 74.30%
         
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            +
            2025-04-03 04:26:27,645 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
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            2025-04-03 04:26:27,645 - INFO - Epoch 15/20
         
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            2025-04-03 04:26:30,224 - INFO - Train Epoch: 15 [0/139 (0%)]	Loss: 0.1892	
         
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            2025-04-03 04:26:47,423 - INFO - Train Epoch: 15 [10/139 (7%)]	Loss: 0.1855	
         
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            2025-04-03 04:27:04,646 - INFO - Train Epoch: 15 [20/139 (14%)]	Loss: 0.1359	
         
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            2025-04-03 04:29:39,793 - INFO - Train Epoch: 15 [110/139 (79%)]	Loss: 0.1678	
         
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            2025-04-03 04:29:57,037 - INFO - Train Epoch: 15 [120/139 (86%)]	Loss: 0.2203	
         
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            2025-04-03 04:30:14,282 - INFO - Train Epoch: 15 [130/139 (94%)]	Loss: 0.2074	
         
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            2025-04-03 04:30:26,712 - INFO - Epoch 15 - Train Loss: 0.1738
         
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            +
            2025-04-03 04:31:12,098 - INFO - Epoch 15 - Validation Accuracy: 77.01%
         
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            +
            2025-04-03 04:31:12,098 - INFO - New best validation accuracy: 77.01%
         
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            +
            2025-04-03 04:31:14,596 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/best_model
         
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            2025-04-03 04:31:16,296 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
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            2025-04-03 04:31:16,296 - INFO - Epoch 16/20
         
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            2025-04-03 04:31:18,880 - INFO - Train Epoch: 16 [0/139 (0%)]	Loss: 0.2957	
         
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            2025-04-03 04:31:36,021 - INFO - Train Epoch: 16 [10/139 (7%)]	Loss: 0.2599	
         
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            2025-04-03 04:31:53,214 - INFO - Train Epoch: 16 [20/139 (14%)]	Loss: 0.1461	
         
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            2025-04-03 04:32:10,421 - INFO - Train Epoch: 16 [30/139 (22%)]	Loss: 0.1998	
         
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            2025-04-03 04:32:44,865 - INFO - Train Epoch: 16 [50/139 (36%)]	Loss: 0.1924	
         
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            2025-04-03 04:33:02,089 - INFO - Train Epoch: 16 [60/139 (43%)]	Loss: 0.1677	
         
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            2025-04-03 04:33:36,598 - INFO - Train Epoch: 16 [80/139 (58%)]	Loss: 0.1536	
         
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            2025-04-03 04:33:53,845 - INFO - Train Epoch: 16 [90/139 (65%)]	Loss: 0.1532	
         
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            2025-04-03 04:34:11,091 - INFO - Train Epoch: 16 [100/139 (72%)]	Loss: 0.1670	
         
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            2025-04-03 04:34:28,344 - INFO - Train Epoch: 16 [110/139 (79%)]	Loss: 0.1153	
         
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            +
            2025-04-03 04:34:45,589 - INFO - Train Epoch: 16 [120/139 (86%)]	Loss: 0.1296	
         
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            2025-04-03 04:35:02,835 - INFO - Train Epoch: 16 [130/139 (94%)]	Loss: 0.1737	
         
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            2025-04-03 04:35:15,274 - INFO - Epoch 16 - Train Loss: 0.1713
         
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            +
            2025-04-03 04:36:00,726 - INFO - Epoch 16 - Validation Accuracy: 76.59%
         
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            +
            2025-04-03 04:36:02,533 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-03 04:36:02,533 - INFO - Epoch 17/20
         
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            +
            2025-04-03 04:36:05,137 - INFO - Train Epoch: 17 [0/139 (0%)]	Loss: 0.1455	
         
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            2025-04-03 04:36:22,334 - INFO - Train Epoch: 17 [10/139 (7%)]	Loss: 0.1546	
         
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            2025-04-03 04:36:39,534 - INFO - Train Epoch: 17 [20/139 (14%)]	Loss: 0.1998	
         
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            2025-04-03 04:36:56,733 - INFO - Train Epoch: 17 [30/139 (22%)]	Loss: 0.1276	
         
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            +
            2025-04-03 04:37:13,950 - INFO - Train Epoch: 17 [40/139 (29%)]	Loss: 0.1946	
         
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            +
            2025-04-03 04:37:31,177 - INFO - Train Epoch: 17 [50/139 (36%)]	Loss: 0.1809	
         
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            2025-04-03 04:37:48,398 - INFO - Train Epoch: 17 [60/139 (43%)]	Loss: 0.2023	
         
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            +
            2025-04-03 04:38:05,622 - INFO - Train Epoch: 17 [70/139 (50%)]	Loss: 0.1823	
         
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            +
            2025-04-03 04:38:22,844 - INFO - Train Epoch: 17 [80/139 (58%)]	Loss: 0.1065	
         
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            2025-04-03 04:38:40,072 - INFO - Train Epoch: 17 [90/139 (65%)]	Loss: 0.2459	
         
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            2025-04-03 04:38:57,302 - INFO - Train Epoch: 17 [100/139 (72%)]	Loss: 0.1396	
         
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            2025-04-03 04:39:14,570 - INFO - Train Epoch: 17 [110/139 (79%)]	Loss: 0.1369	
         
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            +
            2025-04-03 04:39:31,818 - INFO - Train Epoch: 17 [120/139 (86%)]	Loss: 0.1452	
         
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| 333 | 
         
            +
            2025-04-03 04:39:49,057 - INFO - Train Epoch: 17 [130/139 (94%)]	Loss: 0.1603	
         
     | 
| 334 | 
         
            +
            2025-04-03 04:40:01,483 - INFO - Epoch 17 - Train Loss: 0.1608
         
     | 
| 335 | 
         
            +
            2025-04-03 04:40:46,728 - INFO - Epoch 17 - Validation Accuracy: 77.42%
         
     | 
| 336 | 
         
            +
            2025-04-03 04:40:46,728 - INFO - New best validation accuracy: 77.42%
         
     | 
| 337 | 
         
            +
            2025-04-03 04:40:49,289 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/best_model
         
     | 
| 338 | 
         
            +
            2025-04-03 04:40:51,021 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
     | 
| 339 | 
         
            +
            2025-04-03 04:40:51,021 - INFO - Epoch 18/20
         
     | 
| 340 | 
         
            +
            2025-04-03 04:40:53,596 - INFO - Train Epoch: 18 [0/139 (0%)]	Loss: 0.1768	
         
     | 
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            +
            2025-04-03 04:41:10,744 - INFO - Train Epoch: 18 [10/139 (7%)]	Loss: 0.1613	
         
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            +
            2025-04-03 04:41:27,941 - INFO - Train Epoch: 18 [20/139 (14%)]	Loss: 0.1985	
         
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            +
            2025-04-03 04:41:45,138 - INFO - Train Epoch: 18 [30/139 (22%)]	Loss: 0.1849	
         
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            +
            2025-04-03 04:42:02,347 - INFO - Train Epoch: 18 [40/139 (29%)]	Loss: 0.1550	
         
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            +
            2025-04-03 04:42:19,567 - INFO - Train Epoch: 18 [50/139 (36%)]	Loss: 0.1380	
         
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            +
            2025-04-03 04:42:36,790 - INFO - Train Epoch: 18 [60/139 (43%)]	Loss: 0.1527	
         
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| 347 | 
         
            +
            2025-04-03 04:42:54,020 - INFO - Train Epoch: 18 [70/139 (50%)]	Loss: 0.1936	
         
     | 
| 348 | 
         
            +
            2025-04-03 04:43:11,257 - INFO - Train Epoch: 18 [80/139 (58%)]	Loss: 0.1689	
         
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| 349 | 
         
            +
            2025-04-03 04:43:28,504 - INFO - Train Epoch: 18 [90/139 (65%)]	Loss: 0.1880	
         
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            +
            2025-04-03 04:43:45,740 - INFO - Train Epoch: 18 [100/139 (72%)]	Loss: 0.1330	
         
     | 
| 351 | 
         
            +
            2025-04-03 04:44:02,987 - INFO - Train Epoch: 18 [110/139 (79%)]	Loss: 0.1374	
         
     | 
| 352 | 
         
            +
            2025-04-03 04:44:20,230 - INFO - Train Epoch: 18 [120/139 (86%)]	Loss: 0.1223	
         
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| 353 | 
         
            +
            2025-04-03 04:44:37,487 - INFO - Train Epoch: 18 [130/139 (94%)]	Loss: 0.2065	
         
     | 
| 354 | 
         
            +
            2025-04-03 04:44:49,921 - INFO - Epoch 18 - Train Loss: 0.1618
         
     | 
| 355 | 
         
            +
            2025-04-03 04:45:35,549 - INFO - Epoch 18 - Validation Accuracy: 78.32%
         
     | 
| 356 | 
         
            +
            2025-04-03 04:45:35,550 - INFO - New best validation accuracy: 78.32%
         
     | 
| 357 | 
         
            +
            2025-04-03 04:45:37,521 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/best_model
         
     | 
| 358 | 
         
            +
            2025-04-03 04:45:38,913 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
     | 
| 359 | 
         
            +
            2025-04-03 04:45:38,913 - INFO - Epoch 19/20
         
     | 
| 360 | 
         
            +
            2025-04-03 04:45:41,846 - INFO - Train Epoch: 19 [0/139 (0%)]	Loss: 0.1864	
         
     | 
| 361 | 
         
            +
            2025-04-03 04:45:59,174 - INFO - Train Epoch: 19 [10/139 (7%)]	Loss: 0.1124	
         
     | 
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            +
            2025-04-03 04:46:16,434 - INFO - Train Epoch: 19 [20/139 (14%)]	Loss: 0.1610	
         
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| 363 | 
         
            +
            2025-04-03 04:46:33,676 - INFO - Train Epoch: 19 [30/139 (22%)]	Loss: 0.1842	
         
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            +
            2025-04-03 04:46:50,923 - INFO - Train Epoch: 19 [40/139 (29%)]	Loss: 0.2374	
         
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            +
            2025-04-03 04:47:08,191 - INFO - Train Epoch: 19 [50/139 (36%)]	Loss: 0.1881	
         
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            +
            2025-04-03 04:47:25,455 - INFO - Train Epoch: 19 [60/139 (43%)]	Loss: 0.1744	
         
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            +
            2025-04-03 04:47:42,727 - INFO - Train Epoch: 19 [70/139 (50%)]	Loss: 0.1676	
         
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            +
            2025-04-03 04:47:59,985 - INFO - Train Epoch: 19 [80/139 (58%)]	Loss: 0.1444	
         
     | 
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            +
            2025-04-03 04:48:17,256 - INFO - Train Epoch: 19 [90/139 (65%)]	Loss: 0.1523	
         
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            +
            2025-04-03 04:48:34,510 - INFO - Train Epoch: 19 [100/139 (72%)]	Loss: 0.1521	
         
     | 
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            +
            2025-04-03 04:48:51,783 - INFO - Train Epoch: 19 [110/139 (79%)]	Loss: 0.1454	
         
     | 
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            +
            2025-04-03 04:49:09,044 - INFO - Train Epoch: 19 [120/139 (86%)]	Loss: 0.0915	
         
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            +
            2025-04-03 04:49:26,379 - INFO - Train Epoch: 19 [130/139 (94%)]	Loss: 0.1832	
         
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| 374 | 
         
            +
            2025-04-03 04:49:39,026 - INFO - Epoch 19 - Train Loss: 0.1607
         
     | 
| 375 | 
         
            +
            2025-04-03 04:50:24,010 - INFO - Epoch 19 - Validation Accuracy: 76.83%
         
     | 
| 376 | 
         
            +
            2025-04-03 04:50:25,747 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
     | 
| 377 | 
         
            +
            2025-04-03 04:50:25,747 - INFO - Epoch 20/20
         
     | 
| 378 | 
         
            +
            2025-04-03 04:50:28,284 - INFO - Train Epoch: 20 [0/139 (0%)]	Loss: 0.1563	
         
     | 
| 379 | 
         
            +
            2025-04-03 04:50:45,542 - INFO - Train Epoch: 20 [10/139 (7%)]	Loss: 0.1466	
         
     | 
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            +
            2025-04-03 04:51:02,730 - INFO - Train Epoch: 20 [20/139 (14%)]	Loss: 0.1084	
         
     | 
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            +
            2025-04-03 04:51:19,992 - INFO - Train Epoch: 20 [30/139 (22%)]	Loss: 0.1708	
         
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            +
            2025-04-03 04:51:37,219 - INFO - Train Epoch: 20 [40/139 (29%)]	Loss: 0.1509	
         
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            +
            2025-04-03 04:51:54,535 - INFO - Train Epoch: 20 [50/139 (36%)]	Loss: 0.1640	
         
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            +
            2025-04-03 04:52:11,841 - INFO - Train Epoch: 20 [60/139 (43%)]	Loss: 0.1972	
         
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            +
            2025-04-03 04:52:29,090 - INFO - Train Epoch: 20 [70/139 (50%)]	Loss: 0.1213	
         
     | 
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            +
            2025-04-03 04:52:46,454 - INFO - Train Epoch: 20 [80/139 (58%)]	Loss: 0.1498	
         
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            +
            2025-04-03 04:53:03,700 - INFO - Train Epoch: 20 [90/139 (65%)]	Loss: 0.1439	
         
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            +
            2025-04-03 04:53:21,023 - INFO - Train Epoch: 20 [100/139 (72%)]	Loss: 0.1072	
         
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            +
            2025-04-03 04:53:38,284 - INFO - Train Epoch: 20 [110/139 (79%)]	Loss: 0.1488	
         
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            +
            2025-04-03 04:53:55,580 - INFO - Train Epoch: 20 [120/139 (86%)]	Loss: 0.1163	
         
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            +
            2025-04-03 04:54:12,868 - INFO - Train Epoch: 20 [130/139 (94%)]	Loss: 0.1888	
         
     | 
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            +
            2025-04-03 04:54:25,326 - INFO - Epoch 20 - Train Loss: 0.1505
         
     | 
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            +
            2025-04-03 04:55:10,744 - INFO - Epoch 20 - Validation Accuracy: 76.78%
         
     | 
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            +
            2025-04-03 04:55:12,553 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
     | 
| 395 | 
         
            +
            2025-04-03 04:55:57,657 - INFO - Final validation accuracy: 76.78%
         
     | 
| 396 | 
         
            +
            2025-04-03 04:55:57,657 - INFO - Best validation accuracy: 78.32%
         
     | 
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            +
            2025-04-03 04:55:59,372 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_100_percent/checkpoints/checkpoint_last
         
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            2025-04-03 04:55:59,372 - INFO - Training completed
         
     | 
    	
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        exp-rank-16/vit/fewshot_10_percent/checkpoints/best_model/model.pth
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        exp-rank-16/vit/fewshot_10_percent/checkpoints/checkpoint_last/checkpoint.pth
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        exp-rank-16/vit/fewshot_10_percent/checkpoints/checkpoint_last/lora_weights.safetensors
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        exp-rank-16/vit/fewshot_10_percent/checkpoints/checkpoint_last/model.pth
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        exp-rank-16/vit/fewshot_10_percent/training_20250403-005422.log
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| 1 | 
         
            +
            2025-04-03 00:54:22,676 - INFO - Arguments: Namespace(datasets=['aml', 'fundus', 'mammo_calc', 'mammo_mass', 'pneumonia', 'oct', 'pbc', 'bloodmnist', 'breastmnist', 'octmnist', 'pneumoniamnist', 'retinamnist'], use_corruptions=False, severity_range=[1, 3], corruption_types=None, fewshot=0.1, epochs=20, batch_size=256, lr=0.0001, weight_decay=0.0001, temperature=2.0, alpha=0.5, backbone='vit', lora_rank=16, lora_alpha=16, lora_dropout=0.1, device=device(type='cuda', index=5), gpu=5, seed=42, num_workers=4, output_dir='./outputs/exp2/vit/fewshot_10_percent', log_interval=10, save_interval=1, eval_interval=1, resume=None)
         
     | 
| 2 | 
         
            +
            2025-04-03 00:54:22,677 - INFO - Creating dataloaders for datasets: ['aml', 'fundus', 'mammo_calc', 'mammo_mass', 'pneumonia', 'oct', 'pbc', 'bloodmnist', 'breastmnist', 'octmnist', 'pneumoniamnist', 'retinamnist']
         
     | 
| 3 | 
         
            +
            2025-04-03 00:54:51,895 - INFO - Initializing RobustMedClip model
         
     | 
| 4 | 
         
            +
            2025-04-03 00:55:05,615 - INFO - Starting training
         
     | 
| 5 | 
         
            +
            2025-04-03 00:55:05,616 - INFO - Epoch 1/20
         
     | 
| 6 | 
         
            +
            2025-04-03 00:55:08,850 - INFO - Train Epoch: 1 [0/14 (0%)]	Loss: 5.0796	
         
     | 
| 7 | 
         
            +
            2025-04-03 00:55:25,611 - INFO - Train Epoch: 1 [10/14 (71%)]	Loss: 3.8356	
         
     | 
| 8 | 
         
            +
            2025-04-03 00:55:30,371 - INFO - Epoch 1 - Train Loss: 4.2299
         
     | 
| 9 | 
         
            +
            2025-04-03 00:56:14,276 - INFO - Epoch 1 - Validation Accuracy: 5.66%
         
     | 
| 10 | 
         
            +
            2025-04-03 00:56:14,276 - INFO - New best validation accuracy: 5.66%
         
     | 
| 11 | 
         
            +
            2025-04-03 00:56:15,778 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
     | 
| 12 | 
         
            +
            2025-04-03 00:56:17,312 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 13 | 
         
            +
            2025-04-03 00:56:17,312 - INFO - Epoch 2/20
         
     | 
| 14 | 
         
            +
            2025-04-03 00:56:19,847 - INFO - Train Epoch: 2 [0/14 (0%)]	Loss: 3.1250	
         
     | 
| 15 | 
         
            +
            2025-04-03 00:56:36,792 - INFO - Train Epoch: 2 [10/14 (71%)]	Loss: 2.6467	
         
     | 
| 16 | 
         
            +
            2025-04-03 00:56:41,650 - INFO - Epoch 2 - Train Loss: 2.8492
         
     | 
| 17 | 
         
            +
            2025-04-03 00:57:26,069 - INFO - Epoch 2 - Validation Accuracy: 6.78%
         
     | 
| 18 | 
         
            +
            2025-04-03 00:57:26,069 - INFO - New best validation accuracy: 6.78%
         
     | 
| 19 | 
         
            +
            2025-04-03 00:57:27,763 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
     | 
| 20 | 
         
            +
            2025-04-03 00:57:29,531 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 21 | 
         
            +
            2025-04-03 00:57:29,532 - INFO - Epoch 3/20
         
     | 
| 22 | 
         
            +
            2025-04-03 00:57:32,148 - INFO - Train Epoch: 3 [0/14 (0%)]	Loss: 2.6190	
         
     | 
| 23 | 
         
            +
            2025-04-03 00:57:49,227 - INFO - Train Epoch: 3 [10/14 (71%)]	Loss: 2.1194	
         
     | 
| 24 | 
         
            +
            2025-04-03 00:57:54,094 - INFO - Epoch 3 - Train Loss: 2.2764
         
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| 25 | 
         
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            2025-04-03 00:58:38,916 - INFO - Epoch 3 - Validation Accuracy: 7.82%
         
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| 26 | 
         
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            2025-04-03 00:58:38,916 - INFO - New best validation accuracy: 7.82%
         
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            +
            2025-04-03 00:58:40,644 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
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            2025-04-03 00:58:42,327 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
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            2025-04-03 00:58:42,327 - INFO - Epoch 4/20
         
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            +
            2025-04-03 00:58:44,899 - INFO - Train Epoch: 4 [0/14 (0%)]	Loss: 2.0331	
         
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| 31 | 
         
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            2025-04-03 00:59:02,002 - INFO - Train Epoch: 4 [10/14 (71%)]	Loss: 1.9314	
         
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| 32 | 
         
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            2025-04-03 00:59:06,869 - INFO - Epoch 4 - Train Loss: 1.9635
         
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            2025-04-03 00:59:51,778 - INFO - Epoch 4 - Validation Accuracy: 9.24%
         
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            2025-04-03 00:59:51,779 - INFO - New best validation accuracy: 9.24%
         
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| 35 | 
         
            +
            2025-04-03 00:59:53,494 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
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            2025-04-03 00:59:55,213 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
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            2025-04-03 00:59:55,213 - INFO - Epoch 5/20
         
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| 38 | 
         
            +
            2025-04-03 00:59:57,857 - INFO - Train Epoch: 5 [0/14 (0%)]	Loss: 1.8923	
         
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            2025-04-03 01:00:15,068 - INFO - Train Epoch: 5 [10/14 (71%)]	Loss: 1.6179	
         
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            2025-04-03 01:00:19,999 - INFO - Epoch 5 - Train Loss: 1.7733
         
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            2025-04-03 01:01:05,728 - INFO - Epoch 5 - Validation Accuracy: 11.12%
         
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            2025-04-03 01:01:05,729 - INFO - New best validation accuracy: 11.12%
         
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            +
            2025-04-03 01:01:07,407 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
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            2025-04-03 01:01:09,183 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
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            2025-04-03 01:01:09,183 - INFO - Epoch 6/20
         
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            2025-04-03 01:01:11,842 - INFO - Train Epoch: 6 [0/14 (0%)]	Loss: 1.8124	
         
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            2025-04-03 01:01:28,896 - INFO - Train Epoch: 6 [10/14 (71%)]	Loss: 1.6353	
         
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            2025-04-03 01:01:33,748 - INFO - Epoch 6 - Train Loss: 1.6257
         
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            2025-04-03 01:02:18,845 - INFO - Epoch 6 - Validation Accuracy: 13.63%
         
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            2025-04-03 01:02:18,845 - INFO - New best validation accuracy: 13.63%
         
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            +
            2025-04-03 01:02:20,703 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
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            2025-04-03 01:02:23,417 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
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            2025-04-03 01:02:23,417 - INFO - Epoch 7/20
         
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            +
            2025-04-03 01:02:26,044 - INFO - Train Epoch: 7 [0/14 (0%)]	Loss: 1.6416	
         
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            2025-04-03 01:02:43,248 - INFO - Train Epoch: 7 [10/14 (71%)]	Loss: 1.4385	
         
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            2025-04-03 01:02:48,139 - INFO - Epoch 7 - Train Loss: 1.5030
         
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            2025-04-03 01:03:32,630 - INFO - Epoch 7 - Validation Accuracy: 15.23%
         
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            +
            2025-04-03 01:03:32,631 - INFO - New best validation accuracy: 15.23%
         
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| 59 | 
         
            +
            2025-04-03 01:03:34,452 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
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            +
            2025-04-03 01:03:37,035 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
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            2025-04-03 01:03:37,036 - INFO - Epoch 8/20
         
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            +
            2025-04-03 01:03:39,664 - INFO - Train Epoch: 8 [0/14 (0%)]	Loss: 1.4327	
         
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            +
            2025-04-03 01:03:56,901 - INFO - Train Epoch: 8 [10/14 (71%)]	Loss: 1.3814	
         
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            +
            2025-04-03 01:04:01,809 - INFO - Epoch 8 - Train Loss: 1.3888
         
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            +
            2025-04-03 01:04:47,044 - INFO - Epoch 8 - Validation Accuracy: 17.50%
         
     | 
| 66 | 
         
            +
            2025-04-03 01:04:47,044 - INFO - New best validation accuracy: 17.50%
         
     | 
| 67 | 
         
            +
            2025-04-03 01:04:48,981 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
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            +
            2025-04-03 01:04:50,759 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-03 01:04:50,759 - INFO - Epoch 9/20
         
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            +
            2025-04-03 01:04:53,295 - INFO - Train Epoch: 9 [0/14 (0%)]	Loss: 1.2682	
         
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            +
            2025-04-03 01:05:10,493 - INFO - Train Epoch: 9 [10/14 (71%)]	Loss: 1.3281	
         
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            +
            2025-04-03 01:05:15,400 - INFO - Epoch 9 - Train Loss: 1.3033
         
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            +
            2025-04-03 01:06:00,799 - INFO - Epoch 9 - Validation Accuracy: 20.42%
         
     | 
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            +
            2025-04-03 01:06:00,799 - INFO - New best validation accuracy: 20.42%
         
     | 
| 75 | 
         
            +
            2025-04-03 01:06:03,416 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
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            +
            2025-04-03 01:06:05,212 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
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            +
            2025-04-03 01:06:05,212 - INFO - Epoch 10/20
         
     | 
| 78 | 
         
            +
            2025-04-03 01:06:07,809 - INFO - Train Epoch: 10 [0/14 (0%)]	Loss: 1.2300	
         
     | 
| 79 | 
         
            +
            2025-04-03 01:06:24,878 - INFO - Train Epoch: 10 [10/14 (71%)]	Loss: 1.1922	
         
     | 
| 80 | 
         
            +
            2025-04-03 01:06:29,746 - INFO - Epoch 10 - Train Loss: 1.2178
         
     | 
| 81 | 
         
            +
            2025-04-03 01:07:15,039 - INFO - Epoch 10 - Validation Accuracy: 24.70%
         
     | 
| 82 | 
         
            +
            2025-04-03 01:07:15,040 - INFO - New best validation accuracy: 24.70%
         
     | 
| 83 | 
         
            +
            2025-04-03 01:07:16,956 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
     | 
| 84 | 
         
            +
            2025-04-03 01:07:18,634 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 85 | 
         
            +
            2025-04-03 01:07:18,634 - INFO - Epoch 11/20
         
     | 
| 86 | 
         
            +
            2025-04-03 01:07:21,230 - INFO - Train Epoch: 11 [0/14 (0%)]	Loss: 1.0525	
         
     | 
| 87 | 
         
            +
            2025-04-03 01:07:38,378 - INFO - Train Epoch: 11 [10/14 (71%)]	Loss: 1.2115	
         
     | 
| 88 | 
         
            +
            2025-04-03 01:07:43,269 - INFO - Epoch 11 - Train Loss: 1.1439
         
     | 
| 89 | 
         
            +
            2025-04-03 01:08:28,021 - INFO - Epoch 11 - Validation Accuracy: 29.56%
         
     | 
| 90 | 
         
            +
            2025-04-03 01:08:28,022 - INFO - New best validation accuracy: 29.56%
         
     | 
| 91 | 
         
            +
            2025-04-03 01:08:29,860 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
     | 
| 92 | 
         
            +
            2025-04-03 01:08:32,328 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 93 | 
         
            +
            2025-04-03 01:08:32,328 - INFO - Epoch 12/20
         
     | 
| 94 | 
         
            +
            2025-04-03 01:08:34,949 - INFO - Train Epoch: 12 [0/14 (0%)]	Loss: 1.0527	
         
     | 
| 95 | 
         
            +
            2025-04-03 01:08:52,151 - INFO - Train Epoch: 12 [10/14 (71%)]	Loss: 0.9890	
         
     | 
| 96 | 
         
            +
            2025-04-03 01:08:57,062 - INFO - Epoch 12 - Train Loss: 1.0674
         
     | 
| 97 | 
         
            +
            2025-04-03 01:09:42,461 - INFO - Epoch 12 - Validation Accuracy: 33.75%
         
     | 
| 98 | 
         
            +
            2025-04-03 01:09:42,462 - INFO - New best validation accuracy: 33.75%
         
     | 
| 99 | 
         
            +
            2025-04-03 01:09:44,260 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
     | 
| 100 | 
         
            +
            2025-04-03 01:09:46,163 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 101 | 
         
            +
            2025-04-03 01:09:46,163 - INFO - Epoch 13/20
         
     | 
| 102 | 
         
            +
            2025-04-03 01:09:48,770 - INFO - Train Epoch: 13 [0/14 (0%)]	Loss: 0.9353	
         
     | 
| 103 | 
         
            +
            2025-04-03 01:10:05,835 - INFO - Train Epoch: 13 [10/14 (71%)]	Loss: 0.9083	
         
     | 
| 104 | 
         
            +
            2025-04-03 01:10:10,697 - INFO - Epoch 13 - Train Loss: 0.9915
         
     | 
| 105 | 
         
            +
            2025-04-03 01:10:55,652 - INFO - Epoch 13 - Validation Accuracy: 37.20%
         
     | 
| 106 | 
         
            +
            2025-04-03 01:10:55,653 - INFO - New best validation accuracy: 37.20%
         
     | 
| 107 | 
         
            +
            2025-04-03 01:10:57,353 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
     | 
| 108 | 
         
            +
            2025-04-03 01:11:00,360 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 109 | 
         
            +
            2025-04-03 01:11:00,360 - INFO - Epoch 14/20
         
     | 
| 110 | 
         
            +
            2025-04-03 01:11:03,052 - INFO - Train Epoch: 14 [0/14 (0%)]	Loss: 0.8993	
         
     | 
| 111 | 
         
            +
            2025-04-03 01:11:20,012 - INFO - Train Epoch: 14 [10/14 (71%)]	Loss: 0.9838	
         
     | 
| 112 | 
         
            +
            2025-04-03 01:11:24,855 - INFO - Epoch 14 - Train Loss: 0.9328
         
     | 
| 113 | 
         
            +
            2025-04-03 01:12:09,262 - INFO - Epoch 14 - Validation Accuracy: 40.61%
         
     | 
| 114 | 
         
            +
            2025-04-03 01:12:09,262 - INFO - New best validation accuracy: 40.61%
         
     | 
| 115 | 
         
            +
            2025-04-03 01:12:11,066 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
     | 
| 116 | 
         
            +
            2025-04-03 01:12:12,815 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 117 | 
         
            +
            2025-04-03 01:12:12,816 - INFO - Epoch 15/20
         
     | 
| 118 | 
         
            +
            2025-04-03 01:12:15,448 - INFO - Train Epoch: 15 [0/14 (0%)]	Loss: 0.7927	
         
     | 
| 119 | 
         
            +
            2025-04-03 01:12:32,392 - INFO - Train Epoch: 15 [10/14 (71%)]	Loss: 0.9750	
         
     | 
| 120 | 
         
            +
            2025-04-03 01:12:37,227 - INFO - Epoch 15 - Train Loss: 0.8846
         
     | 
| 121 | 
         
            +
            2025-04-03 01:13:21,443 - INFO - Epoch 15 - Validation Accuracy: 43.44%
         
     | 
| 122 | 
         
            +
            2025-04-03 01:13:21,443 - INFO - New best validation accuracy: 43.44%
         
     | 
| 123 | 
         
            +
            2025-04-03 01:13:23,204 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
     | 
| 124 | 
         
            +
            2025-04-03 01:13:25,922 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 125 | 
         
            +
            2025-04-03 01:13:25,922 - INFO - Epoch 16/20
         
     | 
| 126 | 
         
            +
            2025-04-03 01:13:28,587 - INFO - Train Epoch: 16 [0/14 (0%)]	Loss: 0.8614	
         
     | 
| 127 | 
         
            +
            2025-04-03 01:13:45,524 - INFO - Train Epoch: 16 [10/14 (71%)]	Loss: 0.7651	
         
     | 
| 128 | 
         
            +
            2025-04-03 01:13:50,385 - INFO - Epoch 16 - Train Loss: 0.8286
         
     | 
| 129 | 
         
            +
            2025-04-03 01:14:34,468 - INFO - Epoch 16 - Validation Accuracy: 46.43%
         
     | 
| 130 | 
         
            +
            2025-04-03 01:14:34,468 - INFO - New best validation accuracy: 46.43%
         
     | 
| 131 | 
         
            +
            2025-04-03 01:14:36,191 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
     | 
| 132 | 
         
            +
            2025-04-03 01:14:37,956 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 133 | 
         
            +
            2025-04-03 01:14:37,956 - INFO - Epoch 17/20
         
     | 
| 134 | 
         
            +
            2025-04-03 01:14:40,539 - INFO - Train Epoch: 17 [0/14 (0%)]	Loss: 0.7731	
         
     | 
| 135 | 
         
            +
            2025-04-03 01:14:57,533 - INFO - Train Epoch: 17 [10/14 (71%)]	Loss: 0.7870	
         
     | 
| 136 | 
         
            +
            2025-04-03 01:15:02,390 - INFO - Epoch 17 - Train Loss: 0.8008
         
     | 
| 137 | 
         
            +
            2025-04-03 01:15:47,100 - INFO - Epoch 17 - Validation Accuracy: 47.85%
         
     | 
| 138 | 
         
            +
            2025-04-03 01:15:47,101 - INFO - New best validation accuracy: 47.85%
         
     | 
| 139 | 
         
            +
            2025-04-03 01:15:48,777 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
     | 
| 140 | 
         
            +
            2025-04-03 01:15:50,382 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 141 | 
         
            +
            2025-04-03 01:15:50,382 - INFO - Epoch 18/20
         
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| 142 | 
         
            +
            2025-04-03 01:15:53,026 - INFO - Train Epoch: 18 [0/14 (0%)]	Loss: 0.8760	
         
     | 
| 143 | 
         
            +
            2025-04-03 01:16:09,947 - INFO - Train Epoch: 18 [10/14 (71%)]	Loss: 0.6851	
         
     | 
| 144 | 
         
            +
            2025-04-03 01:16:14,773 - INFO - Epoch 18 - Train Loss: 0.7412
         
     | 
| 145 | 
         
            +
            2025-04-03 01:16:59,043 - INFO - Epoch 18 - Validation Accuracy: 49.89%
         
     | 
| 146 | 
         
            +
            2025-04-03 01:16:59,043 - INFO - New best validation accuracy: 49.89%
         
     | 
| 147 | 
         
            +
            2025-04-03 01:17:00,797 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
     | 
| 148 | 
         
            +
            2025-04-03 01:17:02,503 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 149 | 
         
            +
            2025-04-03 01:17:02,504 - INFO - Epoch 19/20
         
     | 
| 150 | 
         
            +
            2025-04-03 01:17:05,125 - INFO - Train Epoch: 19 [0/14 (0%)]	Loss: 0.7171	
         
     | 
| 151 | 
         
            +
            2025-04-03 01:17:22,051 - INFO - Train Epoch: 19 [10/14 (71%)]	Loss: 0.6547	
         
     | 
| 152 | 
         
            +
            2025-04-03 01:17:26,888 - INFO - Epoch 19 - Train Loss: 0.7076
         
     | 
| 153 | 
         
            +
            2025-04-03 01:18:11,118 - INFO - Epoch 19 - Validation Accuracy: 51.86%
         
     | 
| 154 | 
         
            +
            2025-04-03 01:18:11,118 - INFO - New best validation accuracy: 51.86%
         
     | 
| 155 | 
         
            +
            2025-04-03 01:18:12,880 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
     | 
| 156 | 
         
            +
            2025-04-03 01:18:14,605 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 157 | 
         
            +
            2025-04-03 01:18:14,605 - INFO - Epoch 20/20
         
     | 
| 158 | 
         
            +
            2025-04-03 01:18:17,211 - INFO - Train Epoch: 20 [0/14 (0%)]	Loss: 0.6143	
         
     | 
| 159 | 
         
            +
            2025-04-03 01:18:34,127 - INFO - Train Epoch: 20 [10/14 (71%)]	Loss: 0.6985	
         
     | 
| 160 | 
         
            +
            2025-04-03 01:18:38,970 - INFO - Epoch 20 - Train Loss: 0.6661
         
     | 
| 161 | 
         
            +
            2025-04-03 01:19:23,150 - INFO - Epoch 20 - Validation Accuracy: 52.86%
         
     | 
| 162 | 
         
            +
            2025-04-03 01:19:23,150 - INFO - New best validation accuracy: 52.86%
         
     | 
| 163 | 
         
            +
            2025-04-03 01:19:24,754 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/best_model
         
     | 
| 164 | 
         
            +
            2025-04-03 01:19:26,605 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 165 | 
         
            +
            2025-04-03 01:20:11,062 - INFO - Final validation accuracy: 52.86%
         
     | 
| 166 | 
         
            +
            2025-04-03 01:20:11,063 - INFO - Best validation accuracy: 52.86%
         
     | 
| 167 | 
         
            +
            2025-04-03 01:20:13,663 - INFO - Checkpoint saved to outputs/exp2/vit/fewshot_10_percent/checkpoints/checkpoint_last
         
     | 
| 168 | 
         
            +
            2025-04-03 01:20:13,664 - INFO - Training completed
         
     | 
    	
        exp-rank-16/vit/fewshot_30_percent/checkpoints/best_model/checkpoint.pth
    ADDED
    
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            oid sha256:3f523be33716187015978d6529585212749aed3c20adfbcbe2e91dbe4f0427b1
         
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            +
            size 7140630
         
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        exp-rank-16/vit/fewshot_30_percent/checkpoints/best_model/lora_weights.safetensors
    ADDED
    
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            oid sha256:92abd580affe48381f4c6d3a65090727fa97dd357af7106d538418ef041ff97a
         
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            +
            size 3935896
         
     | 
    	
        exp-rank-16/vit/fewshot_30_percent/checkpoints/best_model/model.pth
    ADDED
    
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| 2 | 
         
            +
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    ADDED
    
    | 
         @@ -0,0 +1,3 @@ 
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        exp-rank-16/vit/fewshot_30_percent/checkpoints/checkpoint_last/lora_weights.safetensors
    ADDED
    
    | 
         @@ -0,0 +1,3 @@ 
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|
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|
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