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---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-good-gesturePhaseV5
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# videomae-base-finetuned-good-gesturePhaseV5
This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Accuracy: 0.6871
- Loss: 0.9822
- Accuracy Hold: 0.0
- Accuracy Stroke: 0.0
- Accuracy Recovery: 0.0
- Accuracy Preparation: 0.9221
- Accuracy Unknown: 0.8571
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 1380
### Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss | Accuracy Hold | Accuracy Stroke | Accuracy Recovery | Accuracy Preparation | Accuracy Unknown |
|:-------------:|:-------:|:----:|:--------:|:---------------:|:-------------:|:---------------:|:-----------------:|:--------------------:|:----------------:|
| 1.1475 | 0.0507 | 70 | 0.5597 | 1.2558 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
| 1.2103 | 1.0507 | 140 | 0.5597 | 1.2704 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
| 0.9964 | 2.0507 | 210 | 0.5597 | 1.2142 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
| 0.9975 | 3.0507 | 280 | 0.5970 | 1.0747 | 0.0 | 0.0 | 0.0 | 0.9733 | 0.2692 |
| 1.0538 | 4.0507 | 350 | 0.6642 | 0.9622 | 0.0 | 0.0 | 0.0 | 0.88 | 0.8846 |
| 1.0321 | 5.0507 | 420 | 0.6567 | 0.9451 | 0.0 | 0.0 | 0.0 | 0.8533 | 0.9231 |
| 0.7822 | 6.0507 | 490 | 0.7164 | 0.8797 | 0.0 | 0.0 | 0.0833 | 0.96 | 0.8846 |
| 0.8743 | 7.0507 | 560 | 0.6791 | 0.9399 | 0.0 | 0.0 | 0.0833 | 0.8533 | 1.0 |
| 0.7515 | 8.0507 | 630 | 0.6791 | 0.9290 | 0.0 | 0.0 | 0.0 | 0.8667 | 1.0 |
| 0.8525 | 9.0507 | 700 | 0.7090 | 0.8447 | 0.0 | 0.0 | 0.1667 | 0.9467 | 0.8462 |
| 0.7661 | 10.0507 | 770 | 0.7090 | 0.7857 | 0.0 | 0.0 | 0.1667 | 0.9067 | 0.9615 |
| 0.8363 | 11.0507 | 840 | 0.6866 | 0.8165 | 0.0 | 0.0 | 0.0833 | 0.92 | 0.8462 |
| 0.659 | 12.0507 | 910 | 0.7164 | 0.7951 | 0.0 | 0.0 | 0.1667 | 0.9067 | 1.0 |
| 0.6274 | 13.0507 | 980 | 0.7015 | 0.7754 | 0.0 | 0.0 | 0.0833 | 0.8933 | 1.0 |
| 0.7292 | 14.0507 | 1050 | 0.6791 | 0.8128 | 0.0 | 0.0 | 0.25 | 0.8267 | 1.0 |
| 0.7447 | 15.0507 | 1120 | 0.6866 | 0.7860 | 0.0 | 0.0 | 0.25 | 0.84 | 1.0 |
| 0.5512 | 16.0507 | 1190 | 0.7015 | 0.7839 | 0.0625 | 0.0 | 0.1667 | 0.8667 | 1.0 |
| 0.3404 | 17.0507 | 1260 | 0.7015 | 0.8055 | 0.0 | 0.0 | 0.3333 | 0.8533 | 1.0 |
| 0.4406 | 18.0507 | 1330 | 0.6866 | 0.7800 | 0.0 | 0.0 | 0.1667 | 0.8533 | 1.0 |
| 0.6358 | 19.0362 | 1380 | 0.7015 | 0.7816 | 0.0 | 0.0 | 0.1667 | 0.88 | 1.0 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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