---
license: mit
base_model: microsoft/git-base
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: git-base-captioning
  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-captioning

This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3575
- Wer Score: 0.8322

## 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: 4
- 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Score |
|:-------------:|:------:|:----:|:---------------:|:---------:|
| 7.8992        | 0.3540 | 20   | 7.5466          | 11.1579   |
| 5.9879        | 0.7080 | 40   | 5.6121          | 5.1946    |
| 4.1288        | 1.0619 | 60   | 3.7153          | 4.5433    |
| 2.3477        | 1.4159 | 80   | 1.9989          | 4.0242    |
| 1.0242        | 1.7699 | 100  | 0.8650          | 0.8657    |
| 0.4954        | 2.1239 | 120  | 0.4766          | 0.8676    |
| 0.3365        | 2.4779 | 140  | 0.3993          | 3.7516    |
| 0.4286        | 2.8319 | 160  | 0.3773          | 0.8336    |
| 0.2952        | 3.1858 | 180  | 0.3663          | 0.8329    |
| 0.3996        | 3.5398 | 200  | 0.3619          | 0.8224    |
| 0.2629        | 3.8938 | 220  | 0.3574          | 0.8204    |
| 0.254         | 4.2478 | 240  | 0.3555          | 0.8178    |
| 0.2642        | 4.6018 | 260  | 0.3557          | 0.8132    |
| 0.2725        | 4.9558 | 280  | 0.3533          | 0.8139    |
| 0.2746        | 5.3097 | 300  | 0.3554          | 0.8093    |
| 0.1765        | 5.6637 | 320  | 0.3561          | 0.8244    |
| 0.2981        | 6.0177 | 340  | 0.3542          | 0.8375    |
| 0.1489        | 6.3717 | 360  | 0.3567          | 0.8329    |
| 0.256         | 6.7257 | 380  | 0.3553          | 0.8362    |
| 0.1574        | 7.0796 | 400  | 0.3558          | 0.8342    |
| 0.1836        | 7.4336 | 420  | 0.3566          | 0.8336    |
| 0.1697        | 7.7876 | 440  | 0.3578          | 0.8362    |
| 0.1596        | 8.1416 | 460  | 0.3571          | 0.8414    |
| 0.1628        | 8.4956 | 480  | 0.3579          | 0.8388    |
| 0.1958        | 8.8496 | 500  | 0.3572          | 0.8362    |
| 0.1695        | 9.2035 | 520  | 0.3575          | 0.8303    |
| 0.1686        | 9.5575 | 540  | 0.3576          | 0.8336    |
| 0.2166        | 9.9115 | 560  | 0.3575          | 0.8322    |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1