---
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: 0.1362
- Accuracy: 0.9714

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2638        | 0.06  | 38   | 2.2761          | 0.1143   |
| 1.6112        | 1.06  | 76   | 1.0811          | 0.7143   |
| 0.5768        | 2.06  | 114  | 0.4538          | 0.8857   |
| 0.298         | 3.06  | 152  | 0.4841          | 0.8      |
| 0.0856        | 4.06  | 190  | 0.6021          | 0.8      |
| 0.2283        | 5.06  | 228  | 0.2103          | 0.9286   |
| 0.0559        | 6.06  | 266  | 0.1142          | 0.9714   |
| 0.2279        | 7.06  | 304  | 0.1132          | 0.9714   |
| 0.0145        | 8.06  | 342  | 0.0762          | 0.9714   |
| 0.0057        | 9.06  | 380  | 0.0226          | 1.0      |
| 0.0076        | 10.06 | 418  | 0.1619          | 0.9714   |
| 0.0046        | 11.06 | 456  | 0.1617          | 0.9714   |
| 0.0034        | 12.06 | 494  | 0.1676          | 0.9571   |
| 0.0034        | 13.06 | 532  | 0.1398          | 0.9714   |
| 0.0034        | 14.06 | 570  | 0.1345          | 0.9714   |
| 0.0035        | 15.05 | 600  | 0.1362          | 0.9714   |


### Framework versions

- Transformers 4.33.2
- Pytorch 1.10.0+cu113
- Datasets 2.14.5
- Tokenizers 0.13.3