---
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: 0.1481
- Wer Score: 7.2150

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 0.0359        | 3.12  | 50   | 0.1192          | 0.8131    |
| 0.0174        | 6.25  | 100  | 0.1257          | 3.0654    |
| 0.0132        | 9.38  | 150  | 0.1283          | 0.7850    |
| 0.011         | 12.5  | 200  | 0.1297          | 1.4112    |
| 0.0095        | 15.62 | 250  | 0.1332          | 5.1028    |
| 0.0083        | 18.75 | 300  | 0.1376          | 5.5701    |
| 0.0077        | 21.88 | 350  | 0.1368          | 0.7944    |
| 0.0068        | 25.0  | 400  | 0.1366          | 5.6168    |
| 0.0061        | 28.12 | 450  | 0.1417          | 4.4299    |
| 0.0057        | 31.25 | 500  | 0.1406          | 6.6636    |
| 0.0047        | 34.38 | 550  | 0.1438          | 7.3738    |
| 0.0038        | 37.5  | 600  | 0.1448          | 7.6262    |
| 0.0032        | 40.62 | 650  | 0.1468          | 9.0841    |
| 0.0027        | 43.75 | 700  | 0.1473          | 6.8598    |
| 0.0024        | 46.88 | 750  | 0.1480          | 7.3178    |
| 0.0021        | 50.0  | 800  | 0.1481          | 7.2150    |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1