---
license: apache-2.0
base_model: google/vit-large-patch32-224-in21k
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: vit-large-patch32-224-in21k-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-patch32-224-in21k-finetuned-galaxy10-decals

This model is a fine-tuned version of [google/vit-large-patch32-224-in21k](https://huggingface.co/google/vit-large-patch32-224-in21k) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5281
- Accuracy: 0.8382
- Precision: 0.8372
- Recall: 0.8382
- F1: 0.8356

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.8923        | 0.99  | 31   | 1.6725          | 0.4600   | 0.5537    | 0.4600 | 0.3682 |
| 1.1787        | 1.98  | 62   | 0.9949          | 0.7339   | 0.7513    | 0.7339 | 0.7095 |
| 0.9165        | 2.98  | 93   | 0.7946          | 0.7700   | 0.7694    | 0.7700 | 0.7540 |
| 0.802         | 4.0   | 125  | 0.6747          | 0.7948   | 0.7954    | 0.7948 | 0.7843 |
| 0.7074        | 4.99  | 156  | 0.6196          | 0.8117   | 0.8139    | 0.8117 | 0.8115 |
| 0.6424        | 5.98  | 187  | 0.6205          | 0.8021   | 0.8075    | 0.8021 | 0.7961 |
| 0.6309        | 6.98  | 218  | 0.5760          | 0.8117   | 0.8231    | 0.8117 | 0.8127 |
| 0.5682        | 8.0   | 250  | 0.5748          | 0.8151   | 0.8196    | 0.8151 | 0.8157 |
| 0.5981        | 8.99  | 281  | 0.5704          | 0.8213   | 0.8269    | 0.8213 | 0.8158 |
| 0.547         | 9.98  | 312  | 0.5282          | 0.8377   | 0.8352    | 0.8377 | 0.8345 |
| 0.5067        | 10.98 | 343  | 0.5281          | 0.8382   | 0.8372    | 0.8382 | 0.8356 |
| 0.5066        | 12.0  | 375  | 0.5441          | 0.8247   | 0.8286    | 0.8247 | 0.8219 |
| 0.4919        | 12.99 | 406  | 0.5580          | 0.8157   | 0.8236    | 0.8157 | 0.8155 |
| 0.4508        | 13.98 | 437  | 0.5269          | 0.8303   | 0.8331    | 0.8303 | 0.8279 |
| 0.4415        | 14.98 | 468  | 0.5399          | 0.8185   | 0.8249    | 0.8185 | 0.8203 |
| 0.4178        | 16.0  | 500  | 0.5229          | 0.8320   | 0.8358    | 0.8320 | 0.8301 |
| 0.366         | 16.99 | 531  | 0.5427          | 0.8275   | 0.8281    | 0.8275 | 0.8241 |
| 0.3706        | 17.98 | 562  | 0.5389          | 0.8241   | 0.8242    | 0.8241 | 0.8230 |
| 0.3609        | 18.98 | 593  | 0.5573          | 0.8247   | 0.8262    | 0.8247 | 0.8239 |
| 0.3443        | 20.0  | 625  | 0.5605          | 0.8320   | 0.8325    | 0.8320 | 0.8302 |
| 0.3214        | 20.99 | 656  | 0.5667          | 0.8281   | 0.8295    | 0.8281 | 0.8254 |
| 0.3262        | 21.98 | 687  | 0.5797          | 0.8236   | 0.8237    | 0.8236 | 0.8214 |
| 0.299         | 22.98 | 718  | 0.5938          | 0.8202   | 0.8225    | 0.8202 | 0.8195 |
| 0.2792        | 24.0  | 750  | 0.5909          | 0.8275   | 0.8258    | 0.8275 | 0.8251 |
| 0.2969        | 24.99 | 781  | 0.5658          | 0.8309   | 0.8319    | 0.8309 | 0.8306 |
| 0.2559        | 25.98 | 812  | 0.5936          | 0.8309   | 0.8294    | 0.8309 | 0.8294 |
| 0.2756        | 26.98 | 843  | 0.5898          | 0.8292   | 0.8295    | 0.8292 | 0.8287 |
| 0.254         | 28.0  | 875  | 0.6043          | 0.8303   | 0.8319    | 0.8303 | 0.8289 |
| 0.2674        | 28.99 | 906  | 0.5950          | 0.8371   | 0.8365    | 0.8371 | 0.8353 |
| 0.2432        | 29.76 | 930  | 0.5907          | 0.8360   | 0.8348    | 0.8360 | 0.8345 |


### Framework versions

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