---
license: mit
base_model: microsoft/git-base
tags:
- generated_from_trainer
model-index:
- name: git-base-naruto
  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. -->

# git-base-naruto

This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0279
- Wer Score: 7.0134

## 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: 2e-05
- train_batch_size: 5
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 10
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer Score |
|:-------------:|:-------:|:----:|:---------------:|:---------:|
| 8.5536        | 2.2727  | 50   | 7.1184          | 52.625    |
| 6.2017        | 4.5455  | 100  | 5.0281          | 22.3527   |
| 4.1263        | 6.8182  | 150  | 2.9941          | 21.8616   |
| 2.2013        | 9.0909  | 200  | 1.2700          | 18.7321   |
| 0.7916        | 11.3636 | 250  | 0.3337          | 12.1607   |
| 0.1917        | 13.6364 | 300  | 0.0798          | 4.5357    |
| 0.0458        | 15.9091 | 350  | 0.0356          | 1.0       |
| 0.0142        | 18.1818 | 400  | 0.0278          | 7.25      |
| 0.0066        | 20.4545 | 450  | 0.0287          | 8.4196    |
| 0.0043        | 22.7273 | 500  | 0.0270          | 7.8795    |
| 0.0032        | 25.0    | 550  | 0.0272          | 7.2545    |
| 0.0027        | 27.2727 | 600  | 0.0273          | 7.0179    |
| 0.0023        | 29.5455 | 650  | 0.0271          | 7.2054    |
| 0.002         | 31.8182 | 700  | 0.0275          | 7.0580    |
| 0.0018        | 34.0909 | 750  | 0.0276          | 7.2589    |
| 0.0016        | 36.3636 | 800  | 0.0277          | 7.0312    |
| 0.0015        | 38.6364 | 850  | 0.0277          | 7.0759    |
| 0.0014        | 40.9091 | 900  | 0.0278          | 7.1071    |
| 0.0014        | 43.1818 | 950  | 0.0278          | 7.1161    |
| 0.0013        | 45.4545 | 1000 | 0.0279          | 6.9241    |
| 0.0013        | 47.7273 | 1050 | 0.0279          | 6.9911    |
| 0.0013        | 50.0    | 1100 | 0.0279          | 7.0134    |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1