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videomae-base-short-finetuned-kinetics-finetuned-rwf2000-epochs8-batch8-k
This model is a fine-tuned version of MCG-NJU/videomae-base-short-finetuned-kinetics on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0855
- Accuracy: 0.6764
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 3200
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3699 | 0.06 | 200 | 0.2920 | 0.8925 |
| 0.3127 | 1.06 | 400 | 0.6035 | 0.77 |
| 0.2864 | 2.06 | 600 | 0.5088 | 0.8237 |
| 0.1739 | 3.06 | 800 | 0.6310 | 0.765 |
| 0.1835 | 4.06 | 1000 | 0.3643 | 0.8738 |
| 0.1075 | 5.06 | 1200 | 0.3455 | 0.8862 |
| 0.1362 | 6.06 | 1400 | 0.9145 | 0.75 |
| 0.2958 | 7.06 | 1600 | 0.3544 | 0.895 |
| 0.1571 | 8.06 | 1800 | 0.3748 | 0.8912 |
| 0.2448 | 9.06 | 2000 | 0.3646 | 0.8975 |
| 0.1939 | 10.06 | 2200 | 0.4430 | 0.8762 |
| 0.0666 | 11.06 | 2400 | 0.4916 | 0.8762 |
| 0.1958 | 12.06 | 2600 | 0.5114 | 0.8638 |
| 0.1063 | 13.06 | 2800 | 0.5701 | 0.8612 |
| 0.1047 | 14.06 | 3000 | 0.5226 | 0.8688 |
| 0.0131 | 15.06 | 3200 | 0.4656 | 0.8812 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2
