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

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# vit-base-patch32-224-in21k-finetuned-galaxy10-decals

This model is a fine-tuned version of [google/vit-base-patch32-224-in21k](https://huggingface.co/google/vit-base-patch32-224-in21k) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5055
- Accuracy: 0.8422
- Precision: 0.8413
- Recall: 0.8422
- F1: 0.8406

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.0954        | 0.99  | 31   | 1.9514          | 0.3737   | 0.3322    | 0.3737 | 0.2452 |
| 1.4835        | 1.98  | 62   | 1.3284          | 0.6184   | 0.6016    | 0.6184 | 0.5878 |
| 1.1252        | 2.98  | 93   | 0.9771          | 0.7300   | 0.7400    | 0.7300 | 0.7004 |
| 0.9605        | 4.0   | 125  | 0.8374          | 0.7570   | 0.7754    | 0.7570 | 0.7368 |
| 0.8383        | 4.99  | 156  | 0.7286          | 0.7762   | 0.7728    | 0.7762 | 0.7650 |
| 0.7665        | 5.98  | 187  | 0.7256          | 0.7689   | 0.7683    | 0.7689 | 0.7586 |
| 0.7305        | 6.98  | 218  | 0.6640          | 0.7948   | 0.8031    | 0.7948 | 0.7966 |
| 0.6689        | 8.0   | 250  | 0.6792          | 0.7807   | 0.7859    | 0.7807 | 0.7708 |
| 0.6783        | 8.99  | 281  | 0.5985          | 0.8117   | 0.8076    | 0.8117 | 0.8071 |
| 0.6225        | 9.98  | 312  | 0.6118          | 0.8050   | 0.8036    | 0.8050 | 0.8025 |
| 0.6081        | 10.98 | 343  | 0.5966          | 0.8112   | 0.8108    | 0.8112 | 0.8080 |
| 0.6028        | 12.0  | 375  | 0.5708          | 0.8202   | 0.8239    | 0.8202 | 0.8199 |
| 0.6052        | 12.99 | 406  | 0.6035          | 0.8010   | 0.8116    | 0.8010 | 0.7982 |
| 0.5553        | 13.98 | 437  | 0.5542          | 0.8196   | 0.8199    | 0.8196 | 0.8143 |
| 0.5526        | 14.98 | 468  | 0.5385          | 0.8326   | 0.8346    | 0.8326 | 0.8317 |
| 0.5199        | 16.0  | 500  | 0.5298          | 0.8219   | 0.8192    | 0.8219 | 0.8172 |
| 0.4974        | 16.99 | 531  | 0.5291          | 0.8298   | 0.8306    | 0.8298 | 0.8260 |
| 0.5015        | 17.98 | 562  | 0.5244          | 0.8275   | 0.8280    | 0.8275 | 0.8267 |
| 0.4763        | 18.98 | 593  | 0.5190          | 0.8354   | 0.8357    | 0.8354 | 0.8316 |
| 0.4763        | 20.0  | 625  | 0.5241          | 0.8264   | 0.8286    | 0.8264 | 0.8249 |
| 0.4592        | 20.99 | 656  | 0.5061          | 0.8410   | 0.8439    | 0.8410 | 0.8406 |
| 0.4414        | 21.98 | 687  | 0.5207          | 0.8269   | 0.8265    | 0.8269 | 0.8260 |
| 0.4372        | 22.98 | 718  | 0.5342          | 0.8253   | 0.8283    | 0.8253 | 0.8254 |
| 0.4118        | 24.0  | 750  | 0.5256          | 0.8275   | 0.8291    | 0.8275 | 0.8274 |
| 0.4319        | 24.99 | 781  | 0.5055          | 0.8422   | 0.8413    | 0.8422 | 0.8406 |
| 0.3807        | 25.98 | 812  | 0.5187          | 0.8377   | 0.8375    | 0.8377 | 0.8361 |
| 0.4066        | 26.98 | 843  | 0.5203          | 0.8348   | 0.8333    | 0.8348 | 0.8326 |
| 0.376         | 28.0  | 875  | 0.5128          | 0.8365   | 0.8361    | 0.8365 | 0.8348 |
| 0.3992        | 28.99 | 906  | 0.5108          | 0.8377   | 0.8375    | 0.8377 | 0.8364 |
| 0.3743        | 29.76 | 930  | 0.5087          | 0.8388   | 0.8389    | 0.8388 | 0.8378 |


### Framework versions

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