---
license: apache-2.0
base_model: google/vit-large-patch16-224
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: vit-large-patch16-224-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-large-patch16-224-finetuned-galaxy10-decals

This model is a fine-tuned version of [google/vit-large-patch16-224](https://huggingface.co/google/vit-large-patch16-224) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6404
- Accuracy: 0.8551
- Precision: 0.8525
- Recall: 0.8551
- F1: 0.8526

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.0358        | 0.99  | 31   | 0.7598          | 0.7362   | 0.7425    | 0.7362 | 0.7266 |
| 0.6822        | 1.98  | 62   | 0.6136          | 0.7920   | 0.7972    | 0.7920 | 0.7899 |
| 0.6535        | 2.98  | 93   | 0.5416          | 0.8106   | 0.8140    | 0.8106 | 0.8062 |
| 0.5696        | 4.0   | 125  | 0.5305          | 0.8162   | 0.8195    | 0.8162 | 0.8140 |
| 0.5435        | 4.99  | 156  | 0.5555          | 0.8145   | 0.8242    | 0.8145 | 0.8161 |
| 0.4621        | 5.98  | 187  | 0.5075          | 0.8298   | 0.8344    | 0.8298 | 0.8254 |
| 0.4479        | 6.98  | 218  | 0.5118          | 0.8281   | 0.8291    | 0.8281 | 0.8269 |
| 0.4318        | 8.0   | 250  | 0.5164          | 0.8196   | 0.8255    | 0.8196 | 0.8166 |
| 0.4011        | 8.99  | 281  | 0.5087          | 0.8410   | 0.8369    | 0.8410 | 0.8362 |
| 0.355         | 9.98  | 312  | 0.5063          | 0.8410   | 0.8433    | 0.8410 | 0.8405 |
| 0.3655        | 10.98 | 343  | 0.5419          | 0.8326   | 0.8343    | 0.8326 | 0.8305 |
| 0.3292        | 12.0  | 375  | 0.5134          | 0.8439   | 0.8442    | 0.8439 | 0.8415 |
| 0.3207        | 12.99 | 406  | 0.6285          | 0.8185   | 0.8293    | 0.8185 | 0.8178 |
| 0.2931        | 13.98 | 437  | 0.5627          | 0.8382   | 0.8395    | 0.8382 | 0.8371 |
| 0.2817        | 14.98 | 468  | 0.6059          | 0.8207   | 0.8278    | 0.8207 | 0.8215 |
| 0.2713        | 16.0  | 500  | 0.6140          | 0.8382   | 0.8367    | 0.8382 | 0.8337 |
| 0.233         | 16.99 | 531  | 0.5992          | 0.8382   | 0.8384    | 0.8382 | 0.8374 |
| 0.2313        | 17.98 | 562  | 0.6679          | 0.8292   | 0.8343    | 0.8292 | 0.8278 |
| 0.223         | 18.98 | 593  | 0.6501          | 0.8343   | 0.8386    | 0.8343 | 0.8347 |
| 0.2126        | 20.0  | 625  | 0.6731          | 0.8343   | 0.8304    | 0.8343 | 0.8296 |
| 0.2078        | 20.99 | 656  | 0.6335          | 0.8388   | 0.8410    | 0.8388 | 0.8383 |
| 0.201         | 21.98 | 687  | 0.6120          | 0.8506   | 0.8478    | 0.8506 | 0.8485 |
| 0.2045        | 22.98 | 718  | 0.6590          | 0.8410   | 0.8389    | 0.8410 | 0.8371 |
| 0.1759        | 24.0  | 750  | 0.6478          | 0.8489   | 0.8464    | 0.8489 | 0.8457 |
| 0.1856        | 24.99 | 781  | 0.6604          | 0.8444   | 0.8413    | 0.8444 | 0.8420 |
| 0.1766        | 25.98 | 812  | 0.6922          | 0.8501   | 0.8491    | 0.8501 | 0.8484 |
| 0.1841        | 26.98 | 843  | 0.6485          | 0.8501   | 0.8493    | 0.8501 | 0.8486 |
| 0.1707        | 28.0  | 875  | 0.6393          | 0.8467   | 0.8440    | 0.8467 | 0.8446 |
| 0.1792        | 28.99 | 906  | 0.6404          | 0.8551   | 0.8525    | 0.8551 | 0.8526 |
| 0.1713        | 29.76 | 930  | 0.6398          | 0.8534   | 0.8513    | 0.8534 | 0.8511 |


### Framework versions

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