ALL_NoCrop_ori16F-8B16F-GACWDlr
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: 0.5141
- Accuracy: 0.7530
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 576
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6471 | 0.0833 | 48 | 0.6523 | 0.6280 |
| 0.5835 | 1.0833 | 96 | 0.6113 | 0.6402 |
| 0.4729 | 2.0833 | 144 | 0.5240 | 0.75 |
| 0.3334 | 3.0833 | 192 | 0.4774 | 0.7561 |
| 0.3024 | 4.0833 | 240 | 0.4842 | 0.7866 |
| 0.2645 | 5.0833 | 288 | 0.5221 | 0.7988 |
| 0.22 | 6.0833 | 336 | 0.5060 | 0.7805 |
| 0.1833 | 7.0833 | 384 | 0.4942 | 0.7683 |
| 0.1854 | 8.0833 | 432 | 0.5156 | 0.7744 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1
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Base model
MCG-NJU/videomae-base-finetuned-kinetics