ViViT_default_fold__3__10_epoch_Aug_batch_2_4_BdSLW60
This model is a fine-tuned version of google/vivit-b-16x2-kinetics400 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8711
- Accuracy: 0.8096
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use 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: 9030
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.8734 | 0.1 | 903 | 0.4407 | 0.9340 |
| 0.1847 | 1.1001 | 1807 | 0.0499 | 0.9851 |
| 0.0493 | 2.1 | 2710 | 0.0379 | 0.9900 |
| 0.0795 | 3.1001 | 3614 | 0.0706 | 0.9763 |
| 0.0397 | 4.1 | 4517 | 0.0437 | 0.9925 |
| 0.0008 | 5.1001 | 5421 | 0.0485 | 0.9913 |
| 0.0191 | 6.1 | 6324 | 0.0326 | 0.9913 |
| 0.0513 | 7.1001 | 7228 | 0.0362 | 0.9925 |
| 0.0009 | 8.1 | 8131 | 0.0435 | 0.9938 |
| 0.0022 | 9.0995 | 9030 | 0.0261 | 0.9950 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.1
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Base model
google/vivit-b-16x2-kinetics400