---
library_name: transformers
license: mit
base_model: microsoft/git-base
tags:
- generated_from_trainer
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0344
- Wer Score: 2.2807

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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 |
|:-------------:|:-------:|:----:|:---------------:|:---------:|
| 7.2943        | 4.1667  | 50   | 4.4708          | 21.1278   |
| 2.2992        | 8.3333  | 100  | 0.4252          | 14.8722   |
| 0.1287        | 12.5    | 150  | 0.0311          | 0.6128    |
| 0.0161        | 16.6667 | 200  | 0.0280          | 2.4762    |
| 0.0049        | 20.8333 | 250  | 0.0304          | 2.4561    |
| 0.0022        | 25.0    | 300  | 0.0327          | 2.4085    |
| 0.0016        | 29.1667 | 350  | 0.0328          | 2.3333    |
| 0.0013        | 33.3333 | 400  | 0.0333          | 2.4298    |
| 0.0012        | 37.5    | 450  | 0.0341          | 2.3033    |
| 0.0011        | 41.6667 | 500  | 0.0344          | 2.2569    |
| 0.001         | 45.8333 | 550  | 0.0344          | 2.2744    |
| 0.001         | 50.0    | 600  | 0.0344          | 2.2807    |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1