---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-groub6-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-groub6-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: 2.7184
- Accuracy: 0.1905

## 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: 1
- eval_batch_size: 1
- 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: 132

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.3751        | 0.16  | 21   | 2.9978          | 0.0952   |
| 3.3444        | 1.16  | 42   | 2.9361          | 0.1429   |
| 3.1148        | 2.16  | 63   | 2.8907          | 0.1429   |
| 3.1054        | 3.16  | 84   | 2.8089          | 0.1905   |
| 2.6316        | 4.16  | 105  | 2.7559          | 0.1905   |
| 2.9311        | 5.16  | 126  | 2.7195          | 0.1905   |
| 2.972         | 6.05  | 132  | 2.7184          | 0.1905   |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0+cpu
- Datasets 2.1.0
- Tokenizers 0.13.3