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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-subset |
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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-subset |
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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: 0.7174 |
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- Accuracy: 0.6898 |
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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: 2925 |
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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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| 1.6183 | 0.04 | 118 | 1.5576 | 0.4194 | |
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| 1.4874 | 1.04 | 236 | 1.3517 | 0.4240 | |
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| 1.6523 | 2.04 | 354 | 1.3001 | 0.3364 | |
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| 1.2763 | 3.04 | 472 | 1.1898 | 0.3917 | |
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| 1.2819 | 4.04 | 590 | 1.1945 | 0.5161 | |
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| 1.1196 | 5.04 | 708 | 0.9771 | 0.5668 | |
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| 1.1976 | 6.04 | 826 | 1.1079 | 0.4747 | |
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| 0.8174 | 7.04 | 944 | 0.8705 | 0.6636 | |
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| 0.7923 | 8.04 | 1062 | 0.7827 | 0.6636 | |
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| 0.6052 | 9.04 | 1180 | 0.9455 | 0.6313 | |
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| 0.7902 | 10.04 | 1298 | 0.9512 | 0.6175 | |
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| 0.9501 | 11.04 | 1416 | 0.8058 | 0.7373 | |
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| 1.1756 | 12.04 | 1534 | 0.7674 | 0.7327 | |
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| 0.8482 | 13.04 | 1652 | 0.8455 | 0.6866 | |
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| 0.7657 | 14.04 | 1770 | 0.9124 | 0.6820 | |
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| 0.9752 | 15.04 | 1888 | 0.9788 | 0.6313 | |
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| 0.7176 | 16.04 | 2006 | 0.6860 | 0.7604 | |
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| 0.7682 | 17.04 | 2124 | 0.8052 | 0.7143 | |
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| 0.8862 | 18.04 | 2242 | 0.9102 | 0.6820 | |
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| 0.6609 | 19.04 | 2360 | 0.9360 | 0.6866 | |
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| 0.9678 | 20.04 | 2478 | 0.8441 | 0.6866 | |
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| 0.8617 | 21.04 | 2596 | 0.8136 | 0.7097 | |
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| 0.7097 | 22.04 | 2714 | 0.8615 | 0.7005 | |
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| 0.5089 | 23.04 | 2832 | 0.7796 | 0.7005 | |
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| 0.715 | 24.03 | 2925 | 0.7685 | 0.7235 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 1.13.1 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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