videomae-base-finetuned-SLT-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: 0.4062
- Accuracy: 1.0
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: 944
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 3.8603 | 0.06 | 59 | 3.7147 | 0.025 |
| 3.7747 | 1.06 | 118 | 3.6984 | 0.05 |
| 3.83 | 2.06 | 177 | 3.5418 | 0.075 |
| 3.5065 | 3.06 | 236 | 3.3917 | 0.075 |
| 3.6541 | 4.06 | 295 | 3.3558 | 0.1 |
| 3.5419 | 5.06 | 354 | 3.2460 | 0.15 |
| 3.2664 | 6.06 | 413 | 3.0603 | 0.2 |
| 3.2295 | 7.06 | 472 | 2.7967 | 0.425 |
| 2.829 | 8.06 | 531 | 2.3743 | 0.625 |
| 2.5769 | 9.06 | 590 | 1.9349 | 0.675 |
| 2.0383 | 10.06 | 649 | 1.3413 | 0.875 |
| 1.8328 | 11.06 | 708 | 0.9239 | 0.925 |
| 1.0447 | 12.06 | 767 | 0.6702 | 0.975 |
| 0.8312 | 13.06 | 826 | 0.5127 | 1.0 |
| 0.7203 | 14.06 | 885 | 0.4366 | 1.0 |
| 0.6204 | 15.06 | 944 | 0.4062 | 1.0 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0