videomae-base-finetuned-rwf2000-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: 0.4759
- Accuracy: 0.8075
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
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Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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: 294
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4016 | 0.3367 | 99 | 0.4759 | 0.8075 |
| 0.2963 | 1.3367 | 198 | 0.6920 | 0.72 |
| 0.3408 | 2.3265 | 294 | 0.4544 | 0.7875 |
Framework versions
- Transformers 4.46.2
- Pytorch 1.13.1+cu117
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
MCG-NJU/videomae-base