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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-good-gesturePhaseV5 |
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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-good-gesturePhaseV5 |
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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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- Accuracy: 0.6871 |
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- Loss: 0.9822 |
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- Accuracy Hold: 0.0 |
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- Accuracy Stroke: 0.0 |
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- Accuracy Recovery: 0.0 |
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- Accuracy Preparation: 0.9221 |
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- Accuracy Unknown: 0.8571 |
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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: 1e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 1380 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | Validation Loss | Accuracy Hold | Accuracy Stroke | Accuracy Recovery | Accuracy Preparation | Accuracy Unknown | |
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|:-------------:|:-------:|:----:|:--------:|:---------------:|:-------------:|:---------------:|:-----------------:|:--------------------:|:----------------:| |
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| 1.1475 | 0.0507 | 70 | 0.5597 | 1.2558 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | |
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| 1.2103 | 1.0507 | 140 | 0.5597 | 1.2704 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | |
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| 0.9964 | 2.0507 | 210 | 0.5597 | 1.2142 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 | |
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| 0.9975 | 3.0507 | 280 | 0.5970 | 1.0747 | 0.0 | 0.0 | 0.0 | 0.9733 | 0.2692 | |
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| 1.0538 | 4.0507 | 350 | 0.6642 | 0.9622 | 0.0 | 0.0 | 0.0 | 0.88 | 0.8846 | |
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| 1.0321 | 5.0507 | 420 | 0.6567 | 0.9451 | 0.0 | 0.0 | 0.0 | 0.8533 | 0.9231 | |
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| 0.7822 | 6.0507 | 490 | 0.7164 | 0.8797 | 0.0 | 0.0 | 0.0833 | 0.96 | 0.8846 | |
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| 0.8743 | 7.0507 | 560 | 0.6791 | 0.9399 | 0.0 | 0.0 | 0.0833 | 0.8533 | 1.0 | |
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| 0.7515 | 8.0507 | 630 | 0.6791 | 0.9290 | 0.0 | 0.0 | 0.0 | 0.8667 | 1.0 | |
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| 0.8525 | 9.0507 | 700 | 0.7090 | 0.8447 | 0.0 | 0.0 | 0.1667 | 0.9467 | 0.8462 | |
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| 0.7661 | 10.0507 | 770 | 0.7090 | 0.7857 | 0.0 | 0.0 | 0.1667 | 0.9067 | 0.9615 | |
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| 0.8363 | 11.0507 | 840 | 0.6866 | 0.8165 | 0.0 | 0.0 | 0.0833 | 0.92 | 0.8462 | |
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| 0.659 | 12.0507 | 910 | 0.7164 | 0.7951 | 0.0 | 0.0 | 0.1667 | 0.9067 | 1.0 | |
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| 0.6274 | 13.0507 | 980 | 0.7015 | 0.7754 | 0.0 | 0.0 | 0.0833 | 0.8933 | 1.0 | |
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| 0.7292 | 14.0507 | 1050 | 0.6791 | 0.8128 | 0.0 | 0.0 | 0.25 | 0.8267 | 1.0 | |
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| 0.7447 | 15.0507 | 1120 | 0.6866 | 0.7860 | 0.0 | 0.0 | 0.25 | 0.84 | 1.0 | |
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| 0.5512 | 16.0507 | 1190 | 0.7015 | 0.7839 | 0.0625 | 0.0 | 0.1667 | 0.8667 | 1.0 | |
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| 0.3404 | 17.0507 | 1260 | 0.7015 | 0.8055 | 0.0 | 0.0 | 0.3333 | 0.8533 | 1.0 | |
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| 0.4406 | 18.0507 | 1330 | 0.6866 | 0.7800 | 0.0 | 0.0 | 0.1667 | 0.8533 | 1.0 | |
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| 0.6358 | 19.0362 | 1380 | 0.7015 | 0.7816 | 0.0 | 0.0 | 0.1667 | 0.88 | 1.0 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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