---
license: mit
base_model: microsoft/git-base
tags:
- generated_from_trainer
model-index:
- name: git-base-instagram-cap
  results: []
pipeline_tag: image-to-text
---

<!-- 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-instagram-cap

This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on an [Instagram Caption](https://huggingface.co/datasets/mrSoul7766/instagram_post_captions) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1859
- Wer Score: 1.0566

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 7.3647        | 3.85  | 50   | 4.5576          | 1.0161    |
| 2.4064        | 7.69  | 100  | 0.5626          | 0.9656    |
| 0.2425        | 11.54 | 150  | 0.1644          | 0.8256    |
| 0.0894        | 15.38 | 200  | 0.1631          | 0.8623    |
| 0.0636        | 19.23 | 250  | 0.1660          | 0.8730    |
| 0.0472        | 23.08 | 300  | 0.1701          | 0.8783    |
| 0.0384        | 26.92 | 350  | 0.1743          | 0.8692    |
| 0.0327        | 30.77 | 400  | 0.1778          | 0.8814    |
| 0.0286        | 34.62 | 450  | 0.1791          | 0.8891    |
| 0.0242        | 38.46 | 500  | 0.1818          | 0.8982    |
| 0.0187        | 42.31 | 550  | 0.1831          | 0.9120    |
| 0.0141        | 46.15 | 600  | 0.1856          | 1.0092    |
| 0.012         | 50.0  | 650  | 0.1859          | 1.0566    |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0