---
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: 0.0529
- Wer Score: 1.4091

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- 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 |
|:-------------:|:-------:|:----:|:---------------:|:---------:|
| 7.3586        | 3.7037  | 50   | 4.5383          | 8.8030    |
| 2.3507        | 7.4074  | 100  | 0.4544          | 0.4697    |
| 0.1281        | 11.1111 | 150  | 0.0543          | 0.5152    |
| 0.0161        | 14.8148 | 200  | 0.0491          | 0.4545    |
| 0.0115        | 18.5185 | 250  | 0.0501          | 0.4394    |
| 0.0099        | 22.2222 | 300  | 0.0528          | 0.4697    |
| 0.0085        | 25.9259 | 350  | 0.0536          | 0.4697    |
| 0.0075        | 29.6296 | 400  | 0.0532          | 0.4848    |
| 0.0068        | 33.3333 | 450  | 0.0520          | 0.4697    |
| 0.0061        | 37.0370 | 500  | 0.0528          | 0.6818    |
| 0.0054        | 40.7407 | 550  | 0.0530          | 0.8030    |
| 0.0044        | 44.4444 | 600  | 0.0535          | 1.2121    |
| 0.0038        | 48.1481 | 650  | 0.0529          | 1.4091    |


### Framework versions

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