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videomae-base-finetuned-ucf101-subset
This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3585
- Accuracy: 0.9226
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 3750
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.0046 | 0.04 | 150 | 2.0806 | 0.3143 |
| 1.9549 | 1.04 | 300 | 1.4746 | 0.5429 |
| 0.6873 | 2.04 | 450 | 0.9489 | 0.6714 |
| 1.6042 | 3.04 | 600 | 0.6865 | 0.7571 |
| 0.2082 | 4.04 | 750 | 0.4017 | 0.8857 |
| 0.2805 | 5.04 | 900 | 0.9705 | 0.7714 |
| 0.0062 | 6.04 | 1050 | 0.4833 | 0.8571 |
| 0.2727 | 7.04 | 1200 | 0.8048 | 0.8714 |
| 0.1055 | 8.04 | 1350 | 0.0264 | 0.9857 |
| 0.234 | 9.04 | 1500 | 0.1460 | 0.9714 |
| 0.0015 | 10.04 | 1650 | 0.3039 | 0.9429 |
| 0.0012 | 11.04 | 1800 | 0.2351 | 0.9571 |
| 0.0009 | 12.04 | 1950 | 0.3080 | 0.9286 |
| 0.0009 | 13.04 | 2100 | 0.3477 | 0.9429 |
| 0.036 | 14.04 | 2250 | 0.2366 | 0.9571 |
| 0.0008 | 15.04 | 2400 | 0.4506 | 0.9 |
| 0.0037 | 16.04 | 2550 | 0.2327 | 0.9571 |
| 0.0007 | 17.04 | 2700 | 0.3480 | 0.9286 |
| 0.0007 | 18.04 | 2850 | 0.1762 | 0.9714 |
| 0.0006 | 19.04 | 3000 | 0.0991 | 0.9714 |
| 0.0006 | 20.04 | 3150 | 0.1551 | 0.9714 |
| 0.0006 | 21.04 | 3300 | 0.3023 | 0.9429 |
| 0.0006 | 22.04 | 3450 | 0.1543 | 0.9571 |
| 0.0006 | 23.04 | 3600 | 0.1025 | 0.9571 |
| 0.0006 | 24.04 | 3750 | 0.0876 | 0.9571 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
