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

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: 0.7174
- Accuracy: 0.6898

## 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: 2925

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6183        | 0.04  | 118  | 1.5576          | 0.4194   |
| 1.4874        | 1.04  | 236  | 1.3517          | 0.4240   |
| 1.6523        | 2.04  | 354  | 1.3001          | 0.3364   |
| 1.2763        | 3.04  | 472  | 1.1898          | 0.3917   |
| 1.2819        | 4.04  | 590  | 1.1945          | 0.5161   |
| 1.1196        | 5.04  | 708  | 0.9771          | 0.5668   |
| 1.1976        | 6.04  | 826  | 1.1079          | 0.4747   |
| 0.8174        | 7.04  | 944  | 0.8705          | 0.6636   |
| 0.7923        | 8.04  | 1062 | 0.7827          | 0.6636   |
| 0.6052        | 9.04  | 1180 | 0.9455          | 0.6313   |
| 0.7902        | 10.04 | 1298 | 0.9512          | 0.6175   |
| 0.9501        | 11.04 | 1416 | 0.8058          | 0.7373   |
| 1.1756        | 12.04 | 1534 | 0.7674          | 0.7327   |
| 0.8482        | 13.04 | 1652 | 0.8455          | 0.6866   |
| 0.7657        | 14.04 | 1770 | 0.9124          | 0.6820   |
| 0.9752        | 15.04 | 1888 | 0.9788          | 0.6313   |
| 0.7176        | 16.04 | 2006 | 0.6860          | 0.7604   |
| 0.7682        | 17.04 | 2124 | 0.8052          | 0.7143   |
| 0.8862        | 18.04 | 2242 | 0.9102          | 0.6820   |
| 0.6609        | 19.04 | 2360 | 0.9360          | 0.6866   |
| 0.9678        | 20.04 | 2478 | 0.8441          | 0.6866   |
| 0.8617        | 21.04 | 2596 | 0.8136          | 0.7097   |
| 0.7097        | 22.04 | 2714 | 0.8615          | 0.7005   |
| 0.5089        | 23.04 | 2832 | 0.7796          | 0.7005   |
| 0.715         | 24.03 | 2925 | 0.7685          | 0.7235   |


### Framework versions

- Transformers 4.36.2
- Pytorch 1.13.1
- Datasets 2.16.1
- Tokenizers 0.15.0