videomae-base-finetuned-ucf101-subset
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: 0.1066
- Accuracy: 0.9806
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
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Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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: 370
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.2637 | 0.1027 | 38 | 0.5823 | 0.8 |
0.1646 | 1.1027 | 76 | 0.2318 | 0.9571 |
0.1042 | 2.1027 | 114 | 0.3459 | 0.8571 |
0.1973 | 3.1027 | 152 | 0.2397 | 0.8714 |
0.0685 | 4.1027 | 190 | 0.1367 | 0.9571 |
0.0194 | 5.1027 | 228 | 0.1976 | 0.9286 |
0.0171 | 6.1027 | 266 | 0.1301 | 0.9714 |
0.0035 | 7.1027 | 304 | 0.0791 | 0.9714 |
0.0039 | 8.1027 | 342 | 0.0360 | 0.9857 |
0.0377 | 9.0757 | 370 | 0.0391 | 0.9857 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.1.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
MCG-NJU/videomae-base