---
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-gestureUnitsV3
  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-gestureUnitsV3

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: 0.8932
- Loss: 0.3490
- Accuracy Gunit: 0.5417
- Accuracy Nothing: 1.0

## 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-06
- 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: 340

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss | Accuracy Gunit | Accuracy Nothing |
|:-------------:|:-----:|:----:|:--------:|:---------------:|:--------------:|:----------------:|
| 0.7047        | 0.05  | 17   | 0.5620   | 0.7024          | 0.575          | 0.5556           |
| 0.6958        | 1.05  | 34   | 0.3802   | 0.7165          | 0.725          | 0.2099           |
| 0.6534        | 2.05  | 51   | 0.3719   | 0.7150          | 0.85           | 0.1358           |
| 0.655         | 3.05  | 68   | 0.3223   | 0.7506          | 0.975          | 0.0              |
| 0.6545        | 4.05  | 85   | 0.4298   | 0.6991          | 0.95           | 0.1728           |
| 0.6321        | 5.05  | 102  | 0.4711   | 0.6750          | 0.95           | 0.2346           |
| 0.5883        | 6.05  | 119  | 0.7438   | 0.6142          | 0.9            | 0.6667           |
| 0.5045        | 7.05  | 136  | 0.8182   | 0.5495          | 0.9            | 0.7778           |
| 0.455         | 8.05  | 153  | 0.7190   | 0.5723          | 0.925          | 0.6173           |
| 0.4191        | 9.05  | 170  | 0.9339   | 0.3709          | 0.85           | 0.9753           |
| 0.365         | 10.05 | 187  | 0.9091   | 0.3547          | 0.85           | 0.9383           |
| 0.2593        | 11.05 | 204  | 0.8926   | 0.3632          | 0.85           | 0.9136           |
| 0.2225        | 12.05 | 221  | 0.9421   | 0.2457          | 0.85           | 0.9877           |
| 0.2121        | 13.05 | 238  | 0.9256   | 0.2619          | 0.85           | 0.9630           |
| 0.1506        | 14.05 | 255  | 0.9504   | 0.2190          | 0.85           | 1.0              |
| 0.1335        | 15.05 | 272  | 0.9339   | 0.2221          | 0.85           | 0.9753           |
| 0.1039        | 16.05 | 289  | 0.9421   | 0.2107          | 0.85           | 0.9877           |
| 0.1036        | 17.05 | 306  | 0.9421   | 0.2059          | 0.85           | 0.9877           |
| 0.1019        | 18.05 | 323  | 0.9421   | 0.2063          | 0.85           | 0.9877           |
| 0.1181        | 19.05 | 340  | 0.9504   | 0.2103          | 0.85           | 1.0              |


### Framework versions

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