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

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: 0.3785
- Wer Score: 2.7939

## 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: 10
- eval_batch_size: 10
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 40
- 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 |
|:-------------:|:-------:|:----:|:---------------:|:---------:|
| 6.818         | 4.4444  | 50   | 4.1955          | 4.1407    |
| 2.3051        | 8.8889  | 100  | 0.6527          | 2.5893    |
| 0.2976        | 13.3333 | 150  | 0.2576          | 2.2313    |
| 0.1103        | 17.7778 | 200  | 0.2680          | 2.9372    |
| 0.056         | 22.2222 | 250  | 0.3025          | 2.8351    |
| 0.0323        | 26.6667 | 300  | 0.3286          | 2.9704    |
| 0.0207        | 31.1111 | 350  | 0.3488          | 2.9758    |
| 0.0144        | 35.5556 | 400  | 0.3587          | 2.8506    |
| 0.0111        | 40.0    | 450  | 0.3688          | 2.7654    |
| 0.0091        | 44.4444 | 500  | 0.3762          | 2.8455    |
| 0.0081        | 48.8889 | 550  | 0.3785          | 2.7939    |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1