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videomae-base-finetuned-soccer-action-recognition
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: 0.2554
- Accuracy: 0.9470
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 2728
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.7115 | 0.03 | 85 | 1.4196 | 0.4 |
| 1.0097 | 1.03 | 170 | 0.7807 | 0.6759 |
| 0.6192 | 2.03 | 255 | 0.7952 | 0.7034 |
| 0.4713 | 3.03 | 341 | 0.6536 | 0.7931 |
| 0.3973 | 4.03 | 426 | 0.3638 | 0.8690 |
| 0.3633 | 5.03 | 511 | 0.3616 | 0.8966 |
| 0.2336 | 6.03 | 596 | 0.4579 | 0.8966 |
| 0.1997 | 7.03 | 682 | 1.5970 | 0.6069 |
| 0.2738 | 8.03 | 767 | 0.4102 | 0.8690 |
| 0.2492 | 9.03 | 852 | 0.7651 | 0.8345 |
| 0.1568 | 10.03 | 937 | 0.8561 | 0.8138 |
| 0.1856 | 11.03 | 1023 | 0.2811 | 0.9241 |
| 0.1296 | 12.03 | 1108 | 0.3444 | 0.9172 |
| 0.0782 | 13.03 | 1193 | 0.3423 | 0.9241 |
| 0.14 | 14.03 | 1278 | 0.3122 | 0.9241 |
| 0.0689 | 15.03 | 1364 | 0.3534 | 0.9172 |
| 0.036 | 16.03 | 1449 | 0.4815 | 0.9103 |
| 0.0695 | 17.03 | 1534 | 0.5698 | 0.8828 |
| 0.0618 | 18.03 | 1619 | 0.3053 | 0.9310 |
| 0.0553 | 19.03 | 1705 | 0.3443 | 0.9241 |
| 0.0301 | 20.03 | 1790 | 0.1427 | 0.9586 |
| 0.0412 | 21.03 | 1875 | 0.5619 | 0.8690 |
| 0.0492 | 22.03 | 1960 | 0.5701 | 0.8897 |
| 0.0171 | 23.03 | 2046 | 0.6377 | 0.8690 |
| 0.0181 | 24.03 | 2131 | 0.5981 | 0.8828 |
| 0.0305 | 25.03 | 2216 | 0.3178 | 0.9448 |
| 0.0393 | 26.03 | 2301 | 0.5434 | 0.9103 |
| 0.0248 | 27.03 | 2387 | 0.4097 | 0.9241 |
| 0.0146 | 28.03 | 2472 | 0.4427 | 0.9103 |
| 0.012 | 29.03 | 2557 | 0.5619 | 0.9034 |
| 0.0065 | 30.03 | 2642 | 0.5384 | 0.9103 |
| 0.009 | 31.03 | 2728 | 0.5014 | 0.9172 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
