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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-gesturePhaseV10
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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-gesturePhaseV10
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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: 0.9253
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- Loss: 0.3122
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- Accuracy Hold: 1.0
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- Accuracy Stroke: 0.4286
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- Accuracy Recovery: 0.7895
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- Accuracy Preparation: 1.0
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- Accuracy Unknown: 0.6429
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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: 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: 630
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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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| 1.1344 | 0.2016 | 127 | 0.6900 | 1.0021 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
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| 0.5961 | 1.2016 | 254 | 0.7948 | 0.6022 | 0.2692 | 0.0 | 0.0588 | 0.9873 | 0.8182 |
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| 0.3453 | 2.2016 | 381 | 0.8777 | 0.3925 | 0.8077 | 0.0 | 0.4118 | 0.9747 | 0.8636 |
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| 0.1551 | 3.2016 | 508 | 0.9432 | 0.2178 | 0.9615 | 0.1667 | 0.7059 | 0.9937 | 0.9545 |
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| 0.1213 | 4.1937 | 630 | 0.9476 | 0.2032 | 0.9615 | 0.6667 | 0.7059 | 1.0 | 0.8182 |
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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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