---
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-gesturePhaseV10
  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-gesturePhaseV10

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: 0.9253
- Loss: 0.3122
- Accuracy Hold: 1.0
- Accuracy Stroke: 0.4286
- Accuracy Recovery: 0.7895
- Accuracy Preparation: 1.0
- Accuracy Unknown: 0.6429

## 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: 5e-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: 630

### Training results

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


### Framework versions

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