---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-2
  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-finetuned-2

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: 0.4272
- Accuracy: 0.9182

## 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: 925

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.9244        | 0.2011 | 186  | 0.9936          | 0.5818   |
| 0.3114        | 1.2011 | 372  | 1.0746          | 0.6818   |
| 0.3265        | 2.2011 | 558  | 0.7547          | 0.8364   |
| 0.1401        | 3.2011 | 744  | 0.5196          | 0.9      |
| 0.0014        | 4.1957 | 925  | 0.4272          | 0.9182   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.1.0+cpu
- Datasets 2.19.1
- Tokenizers 0.19.1