videomae-base-OKN-Test-V27
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: 0.0007
- 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: 4
- eval_batch_size: 4
- 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: 400
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3018 | 0.1 | 41 | 0.2653 | 0.8421 |
| 0.4595 | 1.1 | 82 | 0.3113 | 0.7895 |
| 0.4487 | 2.1 | 123 | 0.3188 | 0.8421 |
| 0.1211 | 3.1 | 164 | 0.8331 | 0.8421 |
| 0.309 | 4.1 | 205 | 0.2910 | 0.8947 |
| 0.1185 | 5.1 | 246 | 0.2096 | 0.8421 |
| 0.2193 | 6.1 | 287 | 0.3113 | 0.8947 |
| 0.056 | 7.1 | 328 | 0.0009 | 1.0 |
| 0.002 | 8.1 | 369 | 0.0007 | 1.0 |
| 0.0005 | 9.08 | 400 | 0.0006 | 1.0 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
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Model tree for jayanino/videomae-base-OKN-Test-V27
Base model
MCG-NJU/videomae-base