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README.md
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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-gesturePhaseV3
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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-gesturePhaseV3
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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: 0.6939
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- Loss: 0.9297
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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: 0.8961
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- Accuracy Unknown: 0.9429
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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: 690
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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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| 1.0859 | 0.1014 | 70 | 0.5597 | 1.2821 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
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| 1.1816 | 1.1014 | 140 | 0.5597 | 1.2569 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
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| 0.9776 | 2.1014 | 210 | 0.5597 | 1.1835 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
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| 0.9867 | 3.1014 | 280 | 0.6119 | 1.0721 | 0.0 | 0.0 | 0.0 | 0.96 | 0.3846 |
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| 1.0732 | 4.1014 | 350 | 0.6045 | 1.1086 | 0.0 | 0.0 | 0.0 | 0.7333 | 1.0 |
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| 0.9688 | 5.1014 | 420 | 0.6866 | 0.9288 | 0.0 | 0.0 | 0.0 | 0.9333 | 0.8462 |
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| 0.7733 | 6.1014 | 490 | 0.6567 | 0.9749 | 0.0 | 0.0 | 0.0 | 0.8267 | 1.0 |
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| 0.8798 | 7.1014 | 560 | 0.6866 | 0.8742 | 0.0 | 0.0 | 0.0 | 0.92 | 0.8846 |
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| 0.7771 | 8.1014 | 630 | 0.7015 | 0.8452 | 0.0 | 0.0 | 0.0 | 0.92 | 0.9615 |
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| 1.0448 | 9.0870 | 690 | 0.7239 | 0.8357 | 0.0 | 0.0 | 0.0 | 0.96 | 0.9615 |
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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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