videomae-base-finetuned-ucf101-subset-buddhika-weerasinghe
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: 8.1890
- Accuracy: 0.0
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: 2
- eval_batch_size: 2
- 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: 1800
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
2.4105 | 0.1 | 180 | 1.6309 | 0.4615 |
0.9175 | 1.1 | 360 | 0.4374 | 0.8787 |
0.5086 | 2.1 | 540 | 0.3801 | 0.8905 |
0.2994 | 3.1 | 720 | 0.3462 | 0.8817 |
0.1555 | 4.1 | 900 | 0.3274 | 0.9231 |
0.1337 | 5.1 | 1080 | 0.1435 | 0.9615 |
0.021 | 6.1 | 1260 | 0.1879 | 0.9615 |
0.0485 | 7.1 | 1440 | 0.1055 | 0.9675 |
0.0019 | 8.1 | 1620 | 0.0864 | 0.9763 |
0.0054 | 9.1 | 1800 | 0.0839 | 0.9763 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
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