---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-OKN-Test-V27
  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-OKN-Test-V27

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: 0.0007
- 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: 400

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3018        | 0.1   | 41   | 0.2653          | 0.8421   |
| 0.4595        | 1.1   | 82   | 0.3113          | 0.7895   |
| 0.4487        | 2.1   | 123  | 0.3188          | 0.8421   |
| 0.1211        | 3.1   | 164  | 0.8331          | 0.8421   |
| 0.309         | 4.1   | 205  | 0.2910          | 0.8947   |
| 0.1185        | 5.1   | 246  | 0.2096          | 0.8421   |
| 0.2193        | 6.1   | 287  | 0.3113          | 0.8947   |
| 0.056         | 7.1   | 328  | 0.0009          | 1.0      |
| 0.002         | 8.1   | 369  | 0.0007          | 1.0      |
| 0.0005        | 9.08  | 400  | 0.0006          | 1.0      |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3