---
license: mit
base_model: microsoft/git-base
tags:
- generated_from_trainer
model-index:
- name: GenerativeImage2Text-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. -->

# GenerativeImage2Text-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: 0.0698
- Wer Score: 5.7759

## 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: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer Score |
|:-------------:|:-------:|:----:|:---------------:|:---------:|
| 7.3056        | 3.7037  | 50   | 4.4313          | 24.2069   |
| 2.1534        | 7.4074  | 100  | 0.3158          | 0.4310    |
| 0.0855        | 11.1111 | 150  | 0.0458          | 0.4655    |
| 0.0153        | 14.8148 | 200  | 0.0447          | 0.4655    |
| 0.0109        | 18.5185 | 250  | 0.0492          | 0.4483    |
| 0.0098        | 22.2222 | 300  | 0.0529          | 0.4483    |
| 0.0077        | 25.9259 | 350  | 0.0547          | 0.4828    |
| 0.0069        | 29.6296 | 400  | 0.0567          | 0.4483    |
| 0.0058        | 33.3333 | 450  | 0.0595          | 0.7414    |
| 0.0042        | 37.0370 | 500  | 0.0620          | 2.5517    |
| 0.0036        | 40.7407 | 550  | 0.0654          | 3.1379    |
| 0.0032        | 44.4444 | 600  | 0.0614          | 9.7414    |
| 0.0026        | 48.1481 | 650  | 0.0664          | 6.5517    |
| 0.001         | 51.8519 | 700  | 0.0670          | 7.4828    |
| 0.0006        | 55.5556 | 750  | 0.0662          | 7.5172    |
| 0.0006        | 59.2593 | 800  | 0.0670          | 8.7586    |
| 0.0003        | 62.9630 | 850  | 0.0678          | 7.7414    |
| 0.0003        | 66.6667 | 900  | 0.0685          | 6.7931    |
| 0.0002        | 70.3704 | 950  | 0.0688          | 6.3103    |
| 0.0002        | 74.0741 | 1000 | 0.0689          | 6.4828    |
| 0.0002        | 77.7778 | 1050 | 0.0691          | 6.1724    |
| 0.0002        | 81.4815 | 1100 | 0.0694          | 6.0862    |
| 0.0002        | 85.1852 | 1150 | 0.0695          | 6.1034    |
| 0.0002        | 88.8889 | 1200 | 0.0697          | 5.9828    |
| 0.0002        | 92.5926 | 1250 | 0.0698          | 5.8276    |
| 0.0002        | 96.2963 | 1300 | 0.0698          | 5.7759    |


### Framework versions

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