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End of training

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README.md CHANGED
@@ -32,7 +32,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [pradanaadn/vit-emotional-classifier](https://huggingface.co/pradanaadn/vit-emotional-classifier) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.3140
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  - Accuracy: 0.6312
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  ## Model description
@@ -53,8 +53,8 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 32
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- - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine_with_restarts
@@ -64,11 +64,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 1.1403 | 1.0 | 20 | 1.4137 | 0.5938 |
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- | 1.0421 | 2.0 | 40 | 1.3920 | 0.6188 |
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- | 0.9611 | 3.0 | 60 | 1.3161 | 0.6 |
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- | 0.8988 | 4.0 | 80 | 1.3140 | 0.6312 |
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- | 0.8381 | 5.0 | 100 | 1.2554 | 0.6 |
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [pradanaadn/vit-emotional-classifier](https://huggingface.co/pradanaadn/vit-emotional-classifier) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.1830
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  - Accuracy: 0.6312
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  ## Model description
 
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine_with_restarts
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.9412 | 0.5 | 20 | 1.3606 | 0.575 |
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+ | 0.8621 | 1.0 | 40 | 1.3134 | 0.6125 |
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+ | 0.8025 | 1.5 | 60 | 1.2917 | 0.6062 |
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+ | 0.7077 | 2.0 | 80 | 1.2553 | 0.6062 |
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+ | 0.7259 | 2.5 | 100 | 1.2128 | 0.625 |
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+ | 0.5685 | 3.0 | 120 | 1.2036 | 0.625 |
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+ | 0.5604 | 3.5 | 140 | 1.2057 | 0.6062 |
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+ | 0.4817 | 4.0 | 160 | 1.1830 | 0.6312 |
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+ | 0.4421 | 4.5 | 180 | 1.2004 | 0.5875 |
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+ | 0.4692 | 5.0 | 200 | 1.1568 | 0.6188 |
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  ### Framework versions
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