ucf101_42
This model is a fine-tuned version of MCG-NJU/videomae-base on the ucf101 dataset. It achieves the following results on the evaluation set:
- Loss: 0.8162
- Accuracy: 0.8342
- Test Accuracy: 0.8342
- Df Accuracy: 0.9916
- Unlearn Overall Accuracy: 0.4213
- Unlearn Time: 3533.4948
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: 8
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 292 | 0.8477 | 0.9899 | 0.4183 | 0.4183 | -1 |
| No log | 1.5 | 437 | 0.8162 | 0.9916 | 0.4213 | 0.4213 | -1 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2
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Base model
MCG-NJU/videomae-base