---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-ucf101-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-ucf101-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: 0.0480
- Accuracy: 0.9857

## 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: 8
- eval_batch_size: 8
- 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: 600

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2995        | 0.06  | 38   | 2.1143          | 0.3      |
| 1.6428        | 1.06  | 76   | 1.5030          | 0.3429   |
| 0.6261        | 2.06  | 114  | 0.8121          | 0.6286   |
| 0.4044        | 3.06  | 152  | 0.4910          | 0.7714   |
| 0.3236        | 4.06  | 190  | 0.4558          | 0.8714   |
| 0.1865        | 5.06  | 228  | 0.6773          | 0.8      |
| 0.1479        | 6.06  | 266  | 0.1813          | 0.9571   |
| 0.0418        | 7.06  | 304  | 0.1312          | 0.9714   |
| 0.0718        | 8.06  | 342  | 0.2473          | 0.9286   |
| 0.0596        | 9.06  | 380  | 0.1378          | 0.9714   |
| 0.0079        | 10.06 | 418  | 0.0308          | 0.9857   |
| 0.0134        | 11.06 | 456  | 0.0329          | 1.0      |
| 0.0083        | 12.06 | 494  | 0.0310          | 1.0      |
| 0.0394        | 13.06 | 532  | 0.0543          | 0.9714   |
| 0.004         | 14.06 | 570  | 0.0492          | 0.9857   |
| 0.0043        | 15.05 | 600  | 0.0480          | 0.9857   |


### Framework versions

- Transformers 4.31.0
- Pytorch 1.10.0+cu113
- Datasets 2.14.4
- Tokenizers 0.13.3