---
license: cc-by-nc-4.0
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: 0.3230
- Accuracy: 0.8968

## 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: 1200

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1382        | 0.06  | 75   | 2.1056          | 0.2571   |
| 0.8185        | 1.06  | 150  | 0.6270          | 0.8      |
| 0.5221        | 2.06  | 225  | 0.4341          | 0.8      |
| 0.1069        | 3.06  | 300  | 0.4390          | 0.8714   |
| 0.0195        | 4.06  | 375  | 0.2938          | 0.8571   |
| 0.0097        | 5.06  | 450  | 0.2114          | 0.9      |
| 0.0076        | 6.06  | 525  | 0.1509          | 0.9429   |
| 0.1686        | 7.06  | 600  | 0.2527          | 0.9571   |
| 0.0679        | 8.06  | 675  | 0.0615          | 0.9714   |
| 0.0024        | 9.06  | 750  | 0.1589          | 0.9429   |
| 0.1946        | 10.06 | 825  | 0.4014          | 0.9      |
| 0.154         | 11.06 | 900  | 0.1862          | 0.9429   |
| 0.0021        | 12.06 | 975  | 0.0683          | 0.9857   |
| 0.0019        | 13.06 | 1050 | 0.0541          | 0.9857   |
| 0.002         | 14.06 | 1125 | 0.0473          | 0.9857   |
| 0.0018        | 15.06 | 1200 | 0.0475          | 0.9857   |


### Framework versions

- Transformers 4.29.1
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3