---
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: 0.0372
- Wer Score: 2.1641

## 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Score |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 7.3017        | 4.17  | 50   | 4.4850          | 20.9419   |
| 2.3174        | 8.33  | 100  | 0.4334          | 8.6357    |
| 0.1315        | 12.5  | 150  | 0.0334          | 0.4225    |
| 0.0175        | 16.67 | 200  | 0.0309          | 1.1072    |
| 0.0057        | 20.83 | 250  | 0.0330          | 2.3527    |
| 0.0024        | 25.0  | 300  | 0.0351          | 2.5284    |
| 0.0017        | 29.17 | 350  | 0.0358          | 2.4496    |
| 0.0014        | 33.33 | 400  | 0.0364          | 2.3941    |
| 0.0012        | 37.5  | 450  | 0.0367          | 2.1628    |
| 0.0011        | 41.67 | 500  | 0.0371          | 2.2390    |
| 0.0011        | 45.83 | 550  | 0.0372          | 2.1447    |
| 0.001         | 50.0  | 600  | 0.0372          | 2.1641    |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3