---
license: mit
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: 0.0340
- Wer Score: 2.1498

## 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: 16
- eval_batch_size: 10
- seed: 42
- gradient_accumulation_steps: 2
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 7.321         | 2.13  | 50   | 4.4679          | 21.5557   |
| 2.2294        | 4.26  | 100  | 0.3441          | 11.8745   |
| 0.1021        | 6.38  | 150  | 0.0283          | 0.5672    |
| 0.0187        | 8.51  | 200  | 0.0251          | 0.6018    |
| 0.0086        | 10.64 | 250  | 0.0272          | 3.6786    |
| 0.0038        | 12.77 | 300  | 0.0288          | 6.7119    |
| 0.0019        | 14.89 | 350  | 0.0300          | 4.2023    |
| 0.0011        | 17.02 | 400  | 0.0308          | 4.0768    |
| 0.0009        | 19.15 | 450  | 0.0310          | 3.5980    |
| 0.0007        | 21.28 | 500  | 0.0315          | 3.5723    |
| 0.0007        | 23.4  | 550  | 0.0323          | 2.8835    |
| 0.0006        | 25.53 | 600  | 0.0325          | 2.8399    |
| 0.0006        | 27.66 | 650  | 0.0330          | 2.6274    |
| 0.0006        | 29.79 | 700  | 0.0331          | 2.5416    |
| 0.0006        | 31.91 | 750  | 0.0334          | 2.4213    |
| 0.0006        | 34.04 | 800  | 0.0335          | 2.3214    |
| 0.0006        | 36.17 | 850  | 0.0330          | 2.2330    |
| 0.0006        | 38.3  | 900  | 0.0337          | 2.2254    |
| 0.0006        | 40.43 | 950  | 0.0338          | 2.1652    |
| 0.0006        | 42.55 | 1000 | 0.0340          | 2.1447    |
| 0.0006        | 44.68 | 1050 | 0.0340          | 2.1767    |
| 0.0006        | 46.81 | 1100 | 0.0340          | 2.1536    |
| 0.0006        | 48.94 | 1150 | 0.0340          | 2.1498    |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.12.0
- Tokenizers 0.13.3