videomae-base-finetuned-v2
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: 0.3288
- Accuracy: 0.8392
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: 16
- eval_batch_size: 16
- 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: 104
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6414 | 0.1346 | 14 | 0.9173 | 0.4545 |
| 0.6093 | 1.1346 | 28 | 0.6265 | 0.6364 |
| 0.5066 | 2.1346 | 42 | 0.5984 | 0.6364 |
| 0.3898 | 3.1346 | 56 | 0.4570 | 0.8 |
| 0.4321 | 4.1346 | 70 | 0.6020 | 0.7091 |
| 0.2806 | 5.1346 | 84 | 0.4016 | 0.8364 |
| 0.1498 | 6.1346 | 98 | 0.4253 | 0.8727 |
| 0.2482 | 7.0577 | 104 | 0.4269 | 0.8727 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
MCG-NJU/videomae-base