---
library_name: transformers
license: mit
base_model: microsoft/git-base
tags:
- generated_from_trainer
model-index:
- name: git-base-isg-288
  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-isg-288

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: 0.0937
- Wer Score: 2.7076

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 100

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer Score |
|:-------------:|:-------:|:----:|:---------------:|:---------:|
| 13.4828       | 5.5882  | 50   | 4.2850          | 16.7473   |
| 3.9992        | 11.1176 | 100  | 0.3655          | 0.7942    |
| 0.2368        | 16.7059 | 150  | 0.0692          | 0.6679    |
| 0.0533        | 22.2353 | 200  | 0.0733          | 0.7004    |
| 0.0339        | 27.8235 | 250  | 0.0765          | 0.8520    |
| 0.0249        | 33.3529 | 300  | 0.0795          | 1.8592    |
| 0.0165        | 38.9412 | 350  | 0.0821          | 2.3827    |
| 0.0074        | 44.4706 | 400  | 0.0861          | 2.0542    |
| 0.0034        | 50.0    | 450  | 0.0885          | 3.0361    |
| 0.0023        | 55.5882 | 500  | 0.0909          | 2.4946    |
| 0.0018        | 61.1176 | 550  | 0.0920          | 2.6426    |
| 0.0016        | 66.7059 | 600  | 0.0930          | 2.6354    |
| 0.0015        | 72.2353 | 650  | 0.0930          | 2.2527    |
| 0.0013        | 77.8235 | 700  | 0.0935          | 2.6859    |
| 0.0013        | 83.3529 | 750  | 0.0937          | 2.7726    |
| 0.0012        | 88.9412 | 800  | 0.0937          | 2.7076    |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0