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

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: 0.2106
- Accuracy: 0.9375

## 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: 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: 720

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7142        | 0.12  | 90   | 1.7574          | 0.2      |
| 1.2973        | 1.12  | 180  | 1.0885          | 0.625    |
| 0.7412        | 2.12  | 270  | 0.3997          | 0.9      |
| 0.3196        | 3.12  | 360  | 0.3584          | 0.8875   |
| 0.3123        | 4.12  | 450  | 0.3616          | 0.8875   |
| 0.1454        | 5.12  | 540  | 0.3104          | 0.925    |
| 0.237         | 6.12  | 630  | 0.1316          | 0.95     |
| 0.1447        | 7.12  | 720  | 0.2106          | 0.9375   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2