videomae-base-OKN-Test
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: 0.0017
- 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: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3464 | 0.21 | 21 | 0.3448 | 0.7273 |
| 0.0038 | 1.21 | 42 | 0.0015 | 1.0 |
| 0.0006 | 2.21 | 63 | 0.0005 | 1.0 |
| 0.0003 | 3.21 | 84 | 0.0004 | 1.0 |
| 0.0003 | 4.16 | 100 | 0.0004 | 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
Base model
MCG-NJU/videomae-base