---
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-small-finetuned-kinetics
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-small-finetuned-kinetics-finetuned-judo
  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-small-finetuned-kinetics-finetuned-judo

This model is a fine-tuned version of [MCG-NJU/videomae-small-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-small-finetuned-kinetics) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6398
- Accuracy: 0.7027

## 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: 16
- eval_batch_size: 16
- 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: 190

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.0364        | 0.1053 | 20   | 1.0361          | 0.4324   |
| 0.8371        | 1.1053 | 40   | 0.9787          | 0.5676   |
| 0.6885        | 2.1053 | 60   | 0.9205          | 0.5676   |
| 0.5484        | 3.1053 | 80   | 0.7844          | 0.6216   |
| 0.452         | 4.1053 | 100  | 0.7905          | 0.5676   |
| 0.4008        | 5.1053 | 120  | 0.7258          | 0.6216   |
| 0.291         | 6.1053 | 140  | 0.7222          | 0.6486   |
| 0.211         | 7.1053 | 160  | 0.6974          | 0.7027   |
| 0.2003        | 8.1053 | 180  | 0.6377          | 0.7027   |
| 0.2124        | 9.0526 | 190  | 0.6398          | 0.7027   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Tokenizers 0.21.0