---
license: apache-2.0
base_model: google/vit-base-patch32-384
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: vit-base-patch32-384-finetuned-galaxy10-decals
  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. -->

# vit-base-patch32-384-finetuned-galaxy10-decals

This model is a fine-tuned version of [google/vit-base-patch32-384](https://huggingface.co/google/vit-base-patch32-384) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5542
- Accuracy: 0.8326
- Precision: 0.8324
- Recall: 0.8326
- F1: 0.8298

## 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: 0.0001
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.68          | 0.99  | 31   | 1.3835          | 0.5259   | 0.5014    | 0.5259 | 0.4922 |
| 0.9395        | 1.98  | 62   | 0.8286          | 0.7120   | 0.7053    | 0.7120 | 0.6986 |
| 0.7814        | 2.98  | 93   | 0.7194          | 0.7604   | 0.7515    | 0.7604 | 0.7456 |
| 0.7227        | 4.0   | 125  | 0.6271          | 0.7818   | 0.7913    | 0.7818 | 0.7743 |
| 0.6309        | 4.99  | 156  | 0.5944          | 0.7959   | 0.7959    | 0.7959 | 0.7952 |
| 0.5754        | 5.98  | 187  | 0.5448          | 0.8112   | 0.8165    | 0.8112 | 0.8087 |
| 0.5519        | 6.98  | 218  | 0.5456          | 0.8010   | 0.7990    | 0.8010 | 0.7991 |
| 0.5077        | 8.0   | 250  | 0.5458          | 0.8191   | 0.8229    | 0.8191 | 0.8160 |
| 0.5086        | 8.99  | 281  | 0.5326          | 0.8174   | 0.8181    | 0.8174 | 0.8146 |
| 0.455         | 9.98  | 312  | 0.5379          | 0.8174   | 0.8179    | 0.8174 | 0.8143 |
| 0.4532        | 10.98 | 343  | 0.5239          | 0.8247   | 0.8238    | 0.8247 | 0.8225 |
| 0.4311        | 12.0  | 375  | 0.5290          | 0.8202   | 0.8197    | 0.8202 | 0.8169 |
| 0.4399        | 12.99 | 406  | 0.5355          | 0.8236   | 0.8269    | 0.8236 | 0.8213 |
| 0.4026        | 13.98 | 437  | 0.5132          | 0.8303   | 0.8288    | 0.8303 | 0.8268 |
| 0.3964        | 14.98 | 468  | 0.5101          | 0.8269   | 0.8290    | 0.8269 | 0.8247 |
| 0.3649        | 16.0  | 500  | 0.5296          | 0.8253   | 0.8242    | 0.8253 | 0.8222 |
| 0.3353        | 16.99 | 531  | 0.5319          | 0.8236   | 0.8212    | 0.8236 | 0.8198 |
| 0.3372        | 17.98 | 562  | 0.5203          | 0.8303   | 0.8315    | 0.8303 | 0.8300 |
| 0.3281        | 18.98 | 593  | 0.5428          | 0.8315   | 0.8319    | 0.8315 | 0.8289 |
| 0.3152        | 20.0  | 625  | 0.5453          | 0.8264   | 0.8283    | 0.8264 | 0.8262 |
| 0.3016        | 20.99 | 656  | 0.5464          | 0.8224   | 0.8252    | 0.8224 | 0.8192 |
| 0.2826        | 21.98 | 687  | 0.5473          | 0.8241   | 0.8214    | 0.8241 | 0.8213 |
| 0.2832        | 22.98 | 718  | 0.5596          | 0.8275   | 0.8281    | 0.8275 | 0.8255 |
| 0.2547        | 24.0  | 750  | 0.5768          | 0.8247   | 0.8260    | 0.8247 | 0.8243 |
| 0.2682        | 24.99 | 781  | 0.5693          | 0.8230   | 0.8244    | 0.8230 | 0.8226 |
| 0.245         | 25.98 | 812  | 0.5542          | 0.8326   | 0.8324    | 0.8326 | 0.8298 |
| 0.2575        | 26.98 | 843  | 0.5665          | 0.8241   | 0.8254    | 0.8241 | 0.8234 |
| 0.2386        | 28.0  | 875  | 0.5716          | 0.8309   | 0.8314    | 0.8309 | 0.8293 |
| 0.2452        | 28.99 | 906  | 0.5659          | 0.8303   | 0.8295    | 0.8303 | 0.8279 |
| 0.2394        | 29.76 | 930  | 0.5674          | 0.8315   | 0.8313    | 0.8315 | 0.8294 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.15.1