ucf101_42
This model is a fine-tuned version of MCG-NJU/videomae-large on the ucf101 dataset. It achieves the following results on the evaluation set:
- Loss: 0.7369
- Accuracy: 0.884
- Test Accuracy: 0.884
- Df Accuracy: 0.9510
- Unlearn Overall Accuracy: 0.4665
- Unlearn Time: 6660.9699
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: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
|---|---|---|---|---|---|---|---|
| No log | 1.01 | 64 | 0.5945 | 0.9612 | 0.4648 | 0.4648 | -1 |
| No log | 2.01 | 128 | 0.6980 | 0.9493 | 0.4658 | 0.4658 | -1 |
| No log | 2.97 | 189 | 0.7369 | 0.9510 | 0.4665 | 0.4665 | -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-large