---
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___v3
  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___v3

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: 0.4549
- Accuracy: 0.86

## 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: 4.5e-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: 2000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5109        | 0.05  | 100  | 0.5774          | 0.6637   |
| 0.3791        | 1.05  | 200  | 0.8587          | 0.6625   |
| 0.3991        | 2.05  | 300  | 0.8032          | 0.66     |
| 0.3369        | 3.05  | 400  | 0.4175          | 0.8125   |
| 0.299         | 4.05  | 500  | 0.6348          | 0.7338   |
| 0.2876        | 5.05  | 600  | 0.7832          | 0.7075   |
| 0.4035        | 6.05  | 700  | 0.4888          | 0.7863   |
| 0.2898        | 7.05  | 800  | 0.4414          | 0.8075   |
| 0.2241        | 8.05  | 900  | 0.3882          | 0.845    |
| 0.2225        | 9.05  | 1000 | 0.3793          | 0.8512   |
| 0.2782        | 10.05 | 1100 | 0.5330          | 0.8013   |
| 0.2424        | 11.05 | 1200 | 0.5796          | 0.7887   |
| 0.1123        | 12.05 | 1300 | 0.5412          | 0.8263   |
| 0.2679        | 13.05 | 1400 | 0.6313          | 0.8163   |
| 0.1511        | 14.05 | 1500 | 0.8940          | 0.7525   |
| 0.1491        | 15.05 | 1600 | 0.8924          | 0.7625   |
| 0.0957        | 16.05 | 1700 | 0.8371          | 0.8      |
| 0.1174        | 17.05 | 1800 | 1.0179          | 0.7625   |
| 0.1375        | 18.05 | 1900 | 0.8003          | 0.8      |
| 0.1027        | 19.05 | 2000 | 0.9485          | 0.7837   |


### Framework versions

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