---
language:
- en
license: mit
tags:
- generated_from_trainer
- image-to-text
- image-captioning
base_model: microsoft/git-base
pipeline_tag: image-to-text
model-index:
- name: git-base-instagram-cap
  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-instagram-cap

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: 0.2581
- Wer Score: 3.1462

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 7.3639        | 3.45  | 50   | 4.5936          | 0.9495    |
| 2.389         | 6.9   | 100  | 0.6192          | 0.9387    |
| 0.2242        | 10.34 | 150  | 0.2274          | 0.9036    |
| 0.0883        | 13.79 | 200  | 0.2271          | 0.9084    |
| 0.0643        | 17.24 | 250  | 0.2319          | 0.9387    |
| 0.0493        | 20.69 | 300  | 0.2388          | 0.9501    |
| 0.0409        | 24.14 | 350  | 0.2435          | 0.9522    |
| 0.0344        | 27.59 | 400  | 0.2458          | 0.9616    |
| 0.0311        | 31.03 | 450  | 0.2492          | 1.0027    |
| 0.028         | 34.48 | 500  | 0.2519          | 1.3565    |
| 0.0255        | 37.93 | 550  | 0.2540          | 2.0640    |
| 0.0227        | 41.38 | 600  | 0.2554          | 2.1813    |
| 0.0189        | 44.83 | 650  | 0.2575          | 2.8416    |
| 0.0154        | 48.28 | 700  | 0.2581          | 3.1462    |


### Framework versions

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