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

This model is a fine-tuned version of [google/vit-large-patch32-384](https://huggingface.co./google/vit-large-patch32-384) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6766
- Accuracy: 0.8371
- Precision: 0.8374
- Recall: 0.8371
- F1: 0.8357

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.3342        | 0.99  | 31   | 1.0491          | 0.6313   | 0.6077    | 0.6313 | 0.6052 |
| 0.7979        | 1.98  | 62   | 0.6901          | 0.7672   | 0.7717    | 0.7672 | 0.7652 |
| 0.7197        | 2.98  | 93   | 0.6200          | 0.7785   | 0.7716    | 0.7785 | 0.7705 |
| 0.6321        | 4.0   | 125  | 0.5693          | 0.8061   | 0.8035    | 0.8061 | 0.7957 |
| 0.5768        | 4.99  | 156  | 0.5501          | 0.8112   | 0.8213    | 0.8112 | 0.8134 |
| 0.5173        | 5.98  | 187  | 0.5165          | 0.8213   | 0.8306    | 0.8213 | 0.8202 |
| 0.4781        | 6.98  | 218  | 0.5220          | 0.8106   | 0.8161    | 0.8106 | 0.8090 |
| 0.451         | 8.0   | 250  | 0.5133          | 0.8185   | 0.8227    | 0.8185 | 0.8153 |
| 0.4373        | 8.99  | 281  | 0.5118          | 0.8303   | 0.8325    | 0.8303 | 0.8288 |
| 0.3826        | 9.98  | 312  | 0.5280          | 0.8258   | 0.8269    | 0.8258 | 0.8243 |
| 0.378         | 10.98 | 343  | 0.5477          | 0.8174   | 0.8156    | 0.8174 | 0.8142 |
| 0.3509        | 12.0  | 375  | 0.5437          | 0.8281   | 0.8292    | 0.8281 | 0.8244 |
| 0.3358        | 12.99 | 406  | 0.5627          | 0.8258   | 0.8268    | 0.8258 | 0.8241 |
| 0.3027        | 13.98 | 437  | 0.5558          | 0.8326   | 0.8341    | 0.8326 | 0.8310 |
| 0.3027        | 14.98 | 468  | 0.5703          | 0.8326   | 0.8358    | 0.8326 | 0.8295 |
| 0.2786        | 16.0  | 500  | 0.5791          | 0.8281   | 0.8268    | 0.8281 | 0.8249 |
| 0.2379        | 16.99 | 531  | 0.5864          | 0.8275   | 0.8264    | 0.8275 | 0.8251 |
| 0.2426        | 17.98 | 562  | 0.5984          | 0.8320   | 0.8320    | 0.8320 | 0.8305 |
| 0.2325        | 18.98 | 593  | 0.6217          | 0.8264   | 0.8281    | 0.8264 | 0.8252 |
| 0.2208        | 20.0  | 625  | 0.6166          | 0.8258   | 0.8230    | 0.8258 | 0.8236 |
| 0.2196        | 20.99 | 656  | 0.6308          | 0.8286   | 0.8280    | 0.8286 | 0.8259 |
| 0.2077        | 21.98 | 687  | 0.6242          | 0.8326   | 0.8307    | 0.8326 | 0.8305 |
| 0.2048        | 22.98 | 718  | 0.6801          | 0.8275   | 0.8303    | 0.8275 | 0.8263 |
| 0.1886        | 24.0  | 750  | 0.6615          | 0.8264   | 0.8280    | 0.8264 | 0.8256 |
| 0.2007        | 24.99 | 781  | 0.6847          | 0.8275   | 0.8280    | 0.8275 | 0.8267 |
| 0.1815        | 25.98 | 812  | 0.6669          | 0.8326   | 0.8311    | 0.8326 | 0.8305 |
| 0.1958        | 26.98 | 843  | 0.6766          | 0.8371   | 0.8374    | 0.8371 | 0.8357 |
| 0.1806        | 28.0  | 875  | 0.6679          | 0.8360   | 0.8353    | 0.8360 | 0.8342 |
| 0.1835        | 28.99 | 906  | 0.6767          | 0.8348   | 0.8334    | 0.8348 | 0.8328 |
| 0.1796        | 29.76 | 930  | 0.6787          | 0.8343   | 0.8336    | 0.8343 | 0.8326 |


### Framework versions

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