---
license: mit
tags:
- generated_from_trainer
- vision
- image-to-text
- image-captioning
datasets:
- imagefolder
model-index:
- name: git-base-pokemon
  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-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: 0.1817
- Wer Score: 9.0938

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 7.3974        | 0.7   | 50   | 4.5248          | 4.5234    |
| 2.2794        | 1.4   | 100  | 0.4021          | 5.1680    |
| 0.1697        | 2.1   | 150  | 0.1398          | 1.5039    |
| 0.0816        | 2.8   | 200  | 0.1458          | 9.9570    |
| 0.0556        | 3.5   | 250  | 0.1417          | 2.5234    |
| 0.043         | 4.2   | 300  | 0.1448          | 12.8086   |
| 0.0285        | 4.9   | 350  | 0.1469          | 7.3867    |
| 0.021         | 5.59  | 400  | 0.1505          | 13.0312   |
| 0.0205        | 6.29  | 450  | 0.1499          | 6.3281    |
| 0.0179        | 6.99  | 500  | 0.1527          | 13.0234   |
| 0.0157        | 7.69  | 550  | 0.1552          | 6.3047    |
| 0.015         | 8.39  | 600  | 0.1571          | 6.7656    |
| 0.015         | 9.09  | 650  | 0.1579          | 10.2305   |
| 0.0137        | 9.79  | 700  | 0.1585          | 11.4219   |
| 0.0132        | 10.49 | 750  | 0.1598          | 5.8320    |
| 0.0132        | 11.19 | 800  | 0.1591          | 12.0508   |
| 0.013         | 11.89 | 850  | 0.1612          | 7.9492    |
| 0.0117        | 12.59 | 900  | 0.1621          | 8.1758    |
| 0.0123        | 13.29 | 950  | 0.1632          | 12.9961   |
| 0.0125        | 13.99 | 1000 | 0.1613          | 10.2031   |
| 0.0116        | 14.69 | 1050 | 0.1642          | 5.7930    |
| 0.0112        | 15.38 | 1100 | 0.1636          | 6.1719    |
| 0.0112        | 16.08 | 1150 | 0.1652          | 7.2422    |
| 0.0107        | 16.78 | 1200 | 0.1644          | 12.9961   |
| 0.0108        | 17.48 | 1250 | 0.1661          | 5.0117    |
| 0.0109        | 18.18 | 1300 | 0.1658          | 7.3242    |
| 0.0108        | 18.88 | 1350 | 0.1691          | 6.0547    |
| 0.0101        | 19.58 | 1400 | 0.1690          | 6.9141    |
| 0.0103        | 20.28 | 1450 | 0.1692          | 7.1680    |
| 0.0107        | 20.98 | 1500 | 0.1702          | 12.3281   |
| 0.0099        | 21.68 | 1550 | 0.1708          | 10.75     |
| 0.0103        | 22.38 | 1600 | 0.1714          | 9.5586    |
| 0.0101        | 23.08 | 1650 | 0.1713          | 12.9805   |
| 0.0098        | 23.78 | 1700 | 0.1712          | 11.4883   |
| 0.0095        | 24.48 | 1750 | 0.1711          | 9.3320    |
| 0.0096        | 25.17 | 1800 | 0.1738          | 8.6523    |
| 0.0097        | 25.87 | 1850 | 0.1717          | 11.5078   |
| 0.0091        | 26.57 | 1900 | 0.1735          | 7.9570    |
| 0.0092        | 27.27 | 1950 | 0.1729          | 9.8242    |
| 0.0093        | 27.97 | 2000 | 0.1721          | 10.5078   |
| 0.0087        | 28.67 | 2050 | 0.1732          | 9.3906    |
| 0.009         | 29.37 | 2100 | 0.1760          | 8.0664    |
| 0.009         | 30.07 | 2150 | 0.1769          | 10.5312   |
| 0.0086        | 30.77 | 2200 | 0.1743          | 10.8555   |
| 0.0087        | 31.47 | 2250 | 0.1772          | 10.2188   |
| 0.0089        | 32.17 | 2300 | 0.1757          | 11.6016   |
| 0.0088        | 32.87 | 2350 | 0.1765          | 8.9297    |
| 0.0082        | 33.57 | 2400 | 0.1754          | 9.6484    |
| 0.0082        | 34.27 | 2450 | 0.1770          | 12.3711   |
| 0.0084        | 34.97 | 2500 | 0.1761          | 10.1523   |
| 0.0076        | 35.66 | 2550 | 0.1774          | 9.1055    |
| 0.0077        | 36.36 | 2600 | 0.1788          | 8.7852    |
| 0.0079        | 37.06 | 2650 | 0.1782          | 11.8086   |
| 0.0071        | 37.76 | 2700 | 0.1784          | 10.5234   |
| 0.0075        | 38.46 | 2750 | 0.1789          | 8.8828    |
| 0.0072        | 39.16 | 2800 | 0.1796          | 8.5664    |
| 0.0071        | 39.86 | 2850 | 0.1804          | 9.5391    |
| 0.0069        | 40.56 | 2900 | 0.1796          | 9.4062    |
| 0.0068        | 41.26 | 2950 | 0.1797          | 8.9883    |
| 0.0067        | 41.96 | 3000 | 0.1809          | 10.5273   |
| 0.0062        | 42.66 | 3050 | 0.1801          | 10.4531   |
| 0.0062        | 43.36 | 3100 | 0.1803          | 7.2188    |
| 0.0063        | 44.06 | 3150 | 0.1808          | 8.7930    |
| 0.0058        | 44.76 | 3200 | 0.1804          | 10.5156   |
| 0.0057        | 45.45 | 3250 | 0.1807          | 11.1328   |
| 0.0059        | 46.15 | 3300 | 0.1812          | 8.6875    |
| 0.0055        | 46.85 | 3350 | 0.1811          | 10.2773   |
| 0.0053        | 47.55 | 3400 | 0.1814          | 10.0391   |
| 0.0054        | 48.25 | 3450 | 0.1817          | 8.5391    |
| 0.0053        | 48.95 | 3500 | 0.1818          | 8.9688    |
| 0.005         | 49.65 | 3550 | 0.1817          | 9.0938    |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3