---
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-rwf2000-subset___v1
  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-rwf2000-subset___v1

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: 0.4808
- Accuracy: 0.775

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5205        | 0.2   | 100  | 0.5434          | 0.6837   |
| 0.4084        | 1.2   | 200  | 0.5905          | 0.655    |
| 0.4198        | 2.2   | 300  | 0.4814          | 0.7462   |
| 0.3188        | 3.2   | 400  | 0.5160          | 0.755    |
| 0.2687        | 4.2   | 500  | 0.4808          | 0.775    |


### Framework versions

- Transformers 4.46.2
- Pytorch 1.13.1+cu117
- Datasets 3.1.0
- Tokenizers 0.20.3