---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-groub1-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-groub1-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: 0.3056
- Accuracy: 0.9767

## 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: 2
- eval_batch_size: 2
- 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: 1008

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.8889        | 0.06  | 64   | 3.6733          | 0.0465   |
| 3.8474        | 1.06  | 128  | 3.7358          | 0.0698   |
| 3.7886        | 2.06  | 192  | 3.6336          | 0.0465   |
| 3.7398        | 3.06  | 256  | 3.5894          | 0.0698   |
| 3.7363        | 4.06  | 320  | 3.4637          | 0.0698   |
| 3.6345        | 5.06  | 384  | 3.3875          | 0.0698   |
| 3.2723        | 6.06  | 448  | 3.2156          | 0.1163   |
| 3.2814        | 7.06  | 512  | 2.7291          | 0.7209   |
| 2.7245        | 8.06  | 576  | 1.9657          | 0.8140   |
| 1.8616        | 9.06  | 640  | 1.2883          | 0.8837   |
| 1.3802        | 10.06 | 704  | 0.8116          | 0.9302   |
| 1.0416        | 11.06 | 768  | 0.5877          | 0.9535   |
| 0.6415        | 12.06 | 832  | 0.4426          | 0.9767   |
| 0.5546        | 13.06 | 896  | 0.3599          | 0.9767   |
| 0.4495        | 14.06 | 960  | 0.3212          | 0.9767   |
| 0.2214        | 15.05 | 1008 | 0.3056          | 0.9767   |


### Framework versions

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