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--- |
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license: cc-by-nc-4.0 |
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base_model: MCG-NJU/videomae-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: videomae-base-finetuned-slrbd002 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# videomae-base-finetuned-slrbd002 |
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This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4824 |
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- Accuracy: 0.875 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- training_steps: 1800 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 3.6684 | 0.05 | 90 | 3.6696 | 0.025 | |
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| 3.4781 | 1.05 | 180 | 3.3494 | 0.1313 | |
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| 3.2885 | 2.05 | 270 | 3.1702 | 0.125 | |
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| 2.7847 | 3.05 | 360 | 2.7654 | 0.2562 | |
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| 2.4107 | 4.05 | 450 | 2.6756 | 0.2437 | |
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| 1.7783 | 5.05 | 540 | 1.9950 | 0.4813 | |
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| 1.3054 | 6.05 | 630 | 1.4908 | 0.6188 | |
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| 0.5868 | 7.05 | 720 | 1.4568 | 0.6188 | |
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| 0.4388 | 8.05 | 810 | 0.9511 | 0.7312 | |
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| 0.2187 | 9.05 | 900 | 1.1580 | 0.65 | |
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| 0.1665 | 10.05 | 990 | 0.6565 | 0.8313 | |
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| 0.0959 | 11.05 | 1080 | 0.5731 | 0.8562 | |
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| 0.0273 | 12.05 | 1170 | 0.6637 | 0.8063 | |
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| 0.02 | 13.05 | 1260 | 0.5048 | 0.875 | |
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| 0.0137 | 14.05 | 1350 | 0.4815 | 0.8688 | |
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| 0.0261 | 15.05 | 1440 | 0.5649 | 0.8438 | |
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| 0.013 | 16.05 | 1530 | 0.5419 | 0.8375 | |
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| 0.0123 | 17.05 | 1620 | 0.4864 | 0.8812 | |
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| 0.0527 | 18.05 | 1710 | 0.4725 | 0.8875 | |
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| 0.011 | 19.05 | 1800 | 0.4824 | 0.875 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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