---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-groub13-14-finetuned-SLT-subset
  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-groub13-14-finetuned-SLT-subset

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:
- Loss: 0.9463
- Accuracy: 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-05
- train_batch_size: 4
- eval_batch_size: 4
- 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: 224

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.0689        | 0.07  | 15   | 2.9460          | 0.1      |
| 3.1203        | 1.07  | 30   | 2.7839          | 0.15     |
| 2.8375        | 2.07  | 45   | 2.6131          | 0.2      |
| 2.619         | 3.07  | 60   | 2.5076          | 0.2      |
| 2.455         | 4.07  | 75   | 2.4382          | 0.15     |
| 2.4831        | 5.07  | 90   | 2.3911          | 0.25     |
| 2.5183        | 6.07  | 105  | 2.3353          | 0.3      |
| 2.4267        | 7.07  | 120  | 2.2589          | 0.35     |
| 2.257         | 8.07  | 135  | 2.1845          | 0.4      |
| 2.1795        | 9.07  | 150  | 2.0329          | 0.6      |
| 1.9706        | 10.07 | 165  | 1.7614          | 0.9      |
| 1.7866        | 11.07 | 180  | 1.4249          | 0.95     |
| 1.4293        | 12.07 | 195  | 1.1991          | 0.9      |
| 0.9984        | 13.07 | 210  | 1.0114          | 0.95     |
| 0.9409        | 14.06 | 224  | 0.9463          | 1.0      |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3