---
library_name: transformers
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: 2.1806
- Accuracy: 0.4883

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 960

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 4.2427        | 0.0323  | 31   | 4.2265          | 0.0033   |
| 4.2321        | 1.0323  | 62   | 4.2235          | 0.0100   |
| 4.24          | 2.0323  | 93   | 4.2282          | 0.0100   |
| 4.2445        | 3.0323  | 124  | 4.2250          | 0.0067   |
| 4.2327        | 4.0323  | 155  | 4.2244          | 0.0100   |
| 4.2104        | 5.0323  | 186  | 4.2100          | 0.0201   |
| 4.2374        | 6.0323  | 217  | 4.2022          | 0.0067   |
| 4.1597        | 7.0323  | 248  | 4.1188          | 0.0301   |
| 4.0522        | 8.0323  | 279  | 3.9351          | 0.0702   |
| 3.768         | 9.0323  | 310  | 3.6800          | 0.1070   |
| 3.5147        | 10.0323 | 341  | 3.5416          | 0.1104   |
| 3.2878        | 11.0323 | 372  | 3.7074          | 0.0702   |
| 2.9491        | 12.0323 | 403  | 3.3954          | 0.1070   |
| 2.806         | 13.0323 | 434  | 3.2552          | 0.1706   |
| 2.4568        | 14.0323 | 465  | 3.0654          | 0.2040   |
| 2.3102        | 15.0323 | 496  | 2.7440          | 0.3010   |
| 2.2079        | 16.0323 | 527  | 2.6789          | 0.3144   |
| 1.9638        | 17.0323 | 558  | 2.5920          | 0.3679   |
| 1.7914        | 18.0323 | 589  | 2.6152          | 0.3378   |
| 1.6925        | 19.0323 | 620  | 2.5971          | 0.3445   |
| 1.5124        | 20.0323 | 651  | 2.5767          | 0.3478   |
| 1.4834        | 21.0323 | 682  | 2.4439          | 0.3880   |
| 1.4565        | 22.0323 | 713  | 2.4057          | 0.3846   |
| 1.279         | 23.0323 | 744  | 2.5501          | 0.3545   |
| 1.1477        | 24.0323 | 775  | 2.3247          | 0.4482   |
| 1.2573        | 25.0323 | 806  | 2.1776          | 0.4883   |
| 1.0825        | 26.0323 | 837  | 2.1443          | 0.4783   |
| 1.2121        | 27.0323 | 868  | 2.1490          | 0.4783   |
| 1.0887        | 28.0323 | 899  | 2.1516          | 0.4716   |
| 1.1127        | 29.0323 | 930  | 2.1051          | 0.4883   |
| 0.9905        | 30.0312 | 960  | 2.1170          | 0.4816   |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0