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: 0.9081
- Accuracy: 0.7916
- Test Accuracy: 0.7916
- Df Accuracy: 0.9715
- Unlearn Overall Accuracy: 0.4101
- Unlearn Time: 1384.8440
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: 64
- seed: 42
- gradient_accumulation_steps: 4
- 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 | 1.1 | 14 | 0.9686 | 0.9665 | 0.4066 | 0.4066 | -1 |
| No log | 2.14 | 29 | 0.9081 | 0.9715 | 0.4101 | 0.4101 | -1 |
| No log | 2.55 | 36 | 0.9118 | 0.9715 | 0.4098 | 0.4098 | -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