---
license: mit
tags:
- generated_from_trainer
model-index:
- name: git-base-500img-dataset
  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-500img-dataset

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: 0.4161
- Wer Score: 2.0379

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Score |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 7.0698        | 3.23  | 50   | 4.5086          | 2.5298    |
| 2.6252        | 6.45  | 100  | 0.9823          | 2.2976    |
| 0.5497        | 9.68  | 150  | 0.4681          | 1.6707    |
| 0.2558        | 12.9  | 200  | 0.4162          | 1.7907    |
| 0.1551        | 16.13 | 250  | 0.4052          | 2.0984    |
| 0.1041        | 19.35 | 300  | 0.4054          | 2.0984    |
| 0.0764        | 22.58 | 350  | 0.4088          | 2.0576    |
| 0.0581        | 25.81 | 400  | 0.4054          | 2.0899    |
| 0.0462        | 29.03 | 450  | 0.4092          | 2.0484    |
| 0.0382        | 32.26 | 500  | 0.4118          | 2.1387    |
| 0.0329        | 35.48 | 550  | 0.4126          | 2.1315    |
| 0.0275        | 38.71 | 600  | 0.4139          | 2.0114    |
| 0.0255        | 41.94 | 650  | 0.4173          | 2.0098    |
| 0.0234        | 45.16 | 700  | 0.4155          | 2.0206    |
| 0.0226        | 48.39 | 750  | 0.4161          | 2.0379    |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3