VideoMAE_default_fold__3__10_epoch_Aug_batch_1_4_BdSLW60
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: 0.8015
- Accuracy: 0.8715
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 |
|---|---|---|---|---|
| 7.7232 | 0.1 | 903 | 1.7044 | 0.5940 |
| 1.6336 | 1.1001 | 1807 | 0.3697 | 0.9029 |
| 0.5047 | 2.1 | 2710 | 0.2068 | 0.9402 |
| 0.2142 | 3.1001 | 3614 | 0.1498 | 0.9664 |
| 0.2392 | 4.1 | 4517 | 0.0491 | 0.9863 |
| 0.0409 | 5.1001 | 5421 | 0.0544 | 0.9863 |
| 0.0712 | 6.1 | 6324 | 0.0449 | 0.9888 |
| 0.0478 | 7.1001 | 7228 | 0.0251 | 0.9913 |
| 0.0057 | 8.1 | 8131 | 0.0290 | 0.9925 |
| 0.013 | 9.0995 | 9030 | 0.0503 | 0.9900 |
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
MCG-NJU/videomae-base