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

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: 0.0621
- Wer Score: 4.7174

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Score |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| No log        | 1.48  | 20   | 7.3896          | 132.1522  |
| No log        | 2.96  | 40   | 5.5234          | 1.1413    |
| No log        | 4.44  | 60   | 3.7317          | 1.1196    |
| No log        | 5.93  | 80   | 2.1477          | 1.1304    |
| No log        | 7.41  | 100  | 0.9848          | 1.1087    |
| No log        | 8.89  | 120  | 0.3860          | 1.1304    |
| No log        | 10.37 | 140  | 0.1720          | 1.1087    |
| No log        | 11.85 | 160  | 0.1022          | 1.1196    |
| No log        | 13.33 | 180  | 0.0745          | 1.0543    |
| No log        | 14.81 | 200  | 0.0665          | 2.9239    |
| No log        | 16.3  | 220  | 0.0631          | 2.7174    |
| No log        | 17.78 | 240  | 0.0622          | 2.5326    |
| No log        | 19.26 | 260  | 0.0621          | 4.7174    |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1