---
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: 0.0495
- Wer Score: 4.7488

## 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: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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 |
|:-------------:|:-------:|:----:|:---------------:|:---------:|
| 7.2487        | 1.8182  | 50   | 4.3718          | 22.0605   |
| 2.0953        | 3.6364  | 100  | 0.2876          | 4.0186    |
| 0.0846        | 5.4545  | 150  | 0.0417          | 0.4419    |
| 0.023         | 7.2727  | 200  | 0.0380          | 0.4233    |
| 0.018         | 9.0909  | 250  | 0.0369          | 0.4186    |
| 0.0144        | 10.9091 | 300  | 0.0393          | 3.0093    |
| 0.0116        | 12.7273 | 350  | 0.0407          | 6.9628    |
| 0.0087        | 14.5455 | 400  | 0.0406          | 3.5209    |
| 0.0062        | 16.3636 | 450  | 0.0423          | 14.7023   |
| 0.0034        | 18.1818 | 500  | 0.0429          | 9.0372    |
| 0.0024        | 20.0    | 550  | 0.0471          | 8.3442    |
| 0.0013        | 21.8182 | 600  | 0.0469          | 13.5907   |
| 0.0009        | 23.6364 | 650  | 0.0464          | 14.6186   |
| 0.0005        | 25.4545 | 700  | 0.0468          | 11.1674   |
| 0.0004        | 27.2727 | 750  | 0.0476          | 7.9907    |
| 0.0003        | 29.0909 | 800  | 0.0480          | 7.3070    |
| 0.0003        | 30.9091 | 850  | 0.0480          | 7.2140    |
| 0.0003        | 32.7273 | 900  | 0.0484          | 6.9628    |
| 0.0003        | 34.5455 | 950  | 0.0487          | 6.8512    |
| 0.0003        | 36.3636 | 1000 | 0.0489          | 6.0698    |
| 0.0003        | 38.1818 | 1050 | 0.0491          | 5.4837    |
| 0.0003        | 40.0    | 1100 | 0.0492          | 4.9256    |
| 0.0002        | 41.8182 | 1150 | 0.0493          | 4.7860    |
| 0.0002        | 43.6364 | 1200 | 0.0493          | 4.8140    |
| 0.0002        | 45.4545 | 1250 | 0.0494          | 4.8       |
| 0.0002        | 47.2727 | 1300 | 0.0495          | 4.7581    |
| 0.0002        | 49.0909 | 1350 | 0.0495          | 4.7488    |


### Framework versions

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