---
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-frequency
  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-frequency

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: 0.5657
- Accuracy: 0.7726

## 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: 1480

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8818        | 0.1   | 148  | 0.5919          | 0.7111   |
| 0.6337        | 1.1   | 296  | 0.5929          | 0.7111   |
| 0.6245        | 2.1   | 444  | 0.7150          | 0.6085   |
| 0.6549        | 3.1   | 592  | 0.6096          | 0.7556   |
| 0.658         | 4.1   | 740  | 0.7169          | 0.6735   |
| 0.6981        | 5.1   | 888  | 0.6050          | 0.7726   |
| 0.619         | 6.1   | 1036 | 0.5278          | 0.7709   |
| 0.6163        | 7.1   | 1184 | 0.5167          | 0.7778   |
| 0.3778        | 8.1   | 1332 | 0.5298          | 0.7812   |
| 0.5459        | 9.1   | 1480 | 0.5657          | 0.7726   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.0.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1