picth_vision_checkpoint_3
This model is a fine-tuned version of MCG-NJU/videomae-base-finetuned-kinetics on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0385
- Accuracy: 0.9965
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 15690
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1317 | 0.2 | 3138 | 0.1713 | 0.9632 |
| 0.0002 | 1.2 | 6276 | 0.0348 | 0.9956 |
| 0.026 | 2.2 | 9414 | 0.0616 | 0.9904 |
| 0.0 | 3.2 | 12552 | 0.0348 | 0.9965 |
| 0.0 | 4.2 | 15690 | 0.0385 | 0.9965 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.6.0+cu124
- Datasets 4.4.1
- Tokenizers 0.22.1
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Model tree for miladfa7/picth_vision_checkpoint_3
Base model
MCG-NJU/videomae-base-finetuned-kinetics