---
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-midv-holo-500
  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-midv-holo-500

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: 2.8322
- Accuracy: 0.4264

## 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: Use OptimizerNames.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: 1925

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.2647        | 0.0405  | 78   | 1.2009          | 0.5736   |
| 1.3169        | 1.0405  | 156  | 1.2652          | 0.5078   |
| 1.3004        | 2.0405  | 234  | 1.2036          | 0.5736   |
| 1.1562        | 3.0405  | 312  | 1.1888          | 0.5736   |
| 1.265         | 4.0405  | 390  | 1.2808          | 0.4922   |
| 1.1946        | 5.0405  | 468  | 1.3394          | 0.3295   |
| 1.1222        | 6.0405  | 546  | 1.3204          | 0.5      |
| 1.0244        | 7.0405  | 624  | 1.3697          | 0.3643   |
| 1.1604        | 8.0405  | 702  | 1.3813          | 0.4535   |
| 0.8901        | 9.0405  | 780  | 1.4395          | 0.4225   |
| 0.6032        | 10.0405 | 858  | 1.6609          | 0.4535   |
| 0.6889        | 11.0405 | 936  | 1.7041          | 0.3605   |
| 0.5777        | 12.0405 | 1014 | 1.9075          | 0.3915   |
| 0.4317        | 13.0405 | 1092 | 1.6528          | 0.4690   |
| 0.5087        | 14.0405 | 1170 | 1.6126          | 0.4845   |
| 0.1257        | 15.0405 | 1248 | 2.0637          | 0.4147   |
| 0.3774        | 16.0405 | 1326 | 2.5347          | 0.3721   |
| 0.1259        | 17.0405 | 1404 | 2.6514          | 0.3760   |
| 0.2158        | 18.0405 | 1482 | 2.4290          | 0.4806   |
| 0.0505        | 19.0405 | 1560 | 2.6998          | 0.4225   |
| 0.0563        | 20.0405 | 1638 | 2.6474          | 0.4225   |
| 0.0671        | 21.0405 | 1716 | 2.6487          | 0.4496   |
| 0.1847        | 22.0405 | 1794 | 2.7012          | 0.4496   |
| 0.0041        | 23.0405 | 1872 | 2.7938          | 0.4341   |
| 0.0079        | 24.0275 | 1925 | 2.8322          | 0.4264   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu118
- Datasets 3.2.0
- Tokenizers 0.21.0