---
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: 1.9422
- Accuracy: 0.7011

## 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: 2
- eval_batch_size: 2
- 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: 2640

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.9136        | 0.0254  | 67   | 2.1529          | 0.1096   |
| 1.9987        | 1.0254  | 134  | 1.9985          | 0.2593   |
| 1.0754        | 2.0254  | 201  | 2.1637          | 0.1956   |
| 1.413         | 3.0254  | 268  | 1.9523          | 0.1473   |
| 1.3047        | 4.0254  | 335  | 2.5442          | 0.1956   |
| 1.2488        | 5.0254  | 402  | 2.0563          | 0.2330   |
| 1.0581        | 6.0254  | 469  | 1.9954          | 0.2264   |
| 0.9165        | 7.0254  | 536  | 1.7661          | 0.2769   |
| 1.5722        | 8.0254  | 603  | 2.2872          | 0.2264   |
| 0.9083        | 9.0254  | 670  | 2.1004          | 0.3363   |
| 0.8093        | 10.0254 | 737  | 1.2497          | 0.6549   |
| 0.4925        | 11.0254 | 804  | 3.5720          | 0.2813   |
| 0.4573        | 12.0254 | 871  | 1.5213          | 0.3604   |
| 1.1082        | 13.0254 | 938  | 1.5453          | 0.5934   |
| 0.8066        | 14.0254 | 1005 | 2.9169          | 0.2967   |
| 0.6615        | 15.0254 | 1072 | 2.1412          | 0.5780   |
| 0.146         | 16.0254 | 1139 | 2.5006          | 0.3978   |
| 0.3815        | 17.0254 | 1206 | 1.7907          | 0.5956   |
| 0.2124        | 18.0254 | 1273 | 1.6622          | 0.6527   |
| 0.5304        | 19.0254 | 1340 | 1.8988          | 0.5956   |
| 0.1519        | 20.0254 | 1407 | 2.7940          | 0.3934   |
| 0.486         | 21.0254 | 1474 | 2.6766          | 0.4198   |
| 0.5502        | 22.0254 | 1541 | 2.3451          | 0.5495   |
| 0.7527        | 23.0254 | 1608 | 1.7518          | 0.6462   |
| 0.3194        | 24.0254 | 1675 | 2.0738          | 0.5890   |
| 0.0189        | 25.0254 | 1742 | 2.9264          | 0.5407   |
| 0.2928        | 26.0254 | 1809 | 2.5495          | 0.5451   |
| 0.0036        | 27.0254 | 1876 | 1.8143          | 0.6989   |
| 0.3772        | 28.0254 | 1943 | 2.2384          | 0.6088   |
| 0.0044        | 29.0254 | 2010 | 1.7688          | 0.7033   |
| 0.7291        | 30.0254 | 2077 | 2.0591          | 0.6571   |
| 0.1553        | 31.0254 | 2144 | 2.0690          | 0.6505   |
| 0.5454        | 32.0254 | 2211 | 1.8762          | 0.7055   |
| 0.3096        | 33.0254 | 2278 | 2.2310          | 0.6440   |
| 0.0053        | 34.0254 | 2345 | 2.0907          | 0.6615   |
| 0.0024        | 35.0254 | 2412 | 2.4127          | 0.6022   |
| 0.0022        | 36.0254 | 2479 | 2.0037          | 0.6989   |
| 0.0026        | 37.0254 | 2546 | 2.0130          | 0.6725   |
| 0.0013        | 38.0254 | 2613 | 1.9391          | 0.6967   |
| 0.0017        | 39.0102 | 2640 | 1.9422          | 0.7011   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.0.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1