---
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-gesturePhaseV3
  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-gesturePhaseV3

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: 0.6939
- Loss: 0.9297
- Accuracy Hold: 0.0
- Accuracy Stroke: 0.0
- Accuracy Recovery: 0.0
- Accuracy Preparation: 0.8961
- Accuracy Unknown: 0.9429

## 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: 690

### Training results

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


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1