---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-large-finetuned-right-hand-conflab-v1
  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-large-finetuned-right-hand-conflab-v1

This model is a fine-tuned version of [MCG-NJU/videomae-large](https://huggingface.co/MCG-NJU/videomae-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5240
- Accuracy: 0.6146

## 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: 16
- eval_batch_size: 16
- 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: 1404

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 2.0232        | 0.0420  | 59   | 1.9422          | 0.1942   |
| 1.8426        | 1.0420  | 118  | 1.7418          | 0.3398   |
| 1.7424        | 2.0420  | 177  | 1.6896          | 0.4175   |
| 1.2206        | 3.0420  | 236  | 1.6280          | 0.4466   |
| 1.0738        | 4.0420  | 295  | 1.2310          | 0.5825   |
| 1.0054        | 5.0420  | 354  | 1.3243          | 0.5583   |
| 0.782         | 6.0420  | 413  | 1.1891          | 0.6359   |
| 0.599         | 7.0420  | 472  | 1.1930          | 0.6505   |
| 0.6782        | 8.0420  | 531  | 1.2866          | 0.6359   |
| 0.3033        | 9.0420  | 590  | 1.4236          | 0.5777   |
| 0.2236        | 10.0420 | 649  | 1.3206          | 0.6553   |
| 0.1756        | 11.0420 | 708  | 1.5113          | 0.6602   |
| 0.1341        | 12.0420 | 767  | 1.6544          | 0.6408   |
| 0.0823        | 13.0420 | 826  | 1.6124          | 0.6553   |
| 0.0691        | 14.0420 | 885  | 1.8230          | 0.6456   |


### Framework versions

- Transformers 4.41.0
- Pytorch 1.12.0+cu116
- Datasets 2.19.1
- Tokenizers 0.19.1