---
license: apache-2.0
base_model: google/vit-base-patch16-384
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: vit-base-patch16-384-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-patch16-384-finetuned-galaxy10-decals

This model is a fine-tuned version of [google/vit-base-patch16-384](https://huggingface.co/google/vit-base-patch16-384) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5422
- Accuracy: 0.8613
- Precision: 0.8600
- Recall: 0.8613
- F1: 0.8596

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.5894        | 0.99  | 31   | 1.2732          | 0.5744   | 0.5409    | 0.5744 | 0.5481 |
| 0.8001        | 1.98  | 62   | 0.6184          | 0.7976   | 0.7934    | 0.7976 | 0.7880 |
| 0.6895        | 2.98  | 93   | 0.5823          | 0.8067   | 0.7991    | 0.8067 | 0.7955 |
| 0.6259        | 4.0   | 125  | 0.4910          | 0.8433   | 0.8427    | 0.8433 | 0.8368 |
| 0.556         | 4.99  | 156  | 0.4874          | 0.8467   | 0.8465    | 0.8467 | 0.8465 |
| 0.5116        | 5.98  | 187  | 0.4734          | 0.8546   | 0.8569    | 0.8546 | 0.8518 |
| 0.4877        | 6.98  | 218  | 0.4539          | 0.8461   | 0.8429    | 0.8461 | 0.8428 |
| 0.4383        | 8.0   | 250  | 0.4716          | 0.8377   | 0.8399    | 0.8377 | 0.8345 |
| 0.4267        | 8.99  | 281  | 0.4355          | 0.8602   | 0.8576    | 0.8602 | 0.8559 |
| 0.4022        | 9.98  | 312  | 0.4758          | 0.8377   | 0.8377    | 0.8377 | 0.8356 |
| 0.3811        | 10.98 | 343  | 0.4538          | 0.8495   | 0.8471    | 0.8495 | 0.8474 |
| 0.3612        | 12.0  | 375  | 0.4808          | 0.8439   | 0.8412    | 0.8439 | 0.8399 |
| 0.363         | 12.99 | 406  | 0.4751          | 0.8467   | 0.8502    | 0.8467 | 0.8458 |
| 0.3198        | 13.98 | 437  | 0.4800          | 0.8489   | 0.8497    | 0.8489 | 0.8450 |
| 0.3192        | 14.98 | 468  | 0.4834          | 0.8574   | 0.8580    | 0.8574 | 0.8570 |
| 0.3041        | 16.0  | 500  | 0.4879          | 0.8495   | 0.8500    | 0.8495 | 0.8443 |
| 0.2607        | 16.99 | 531  | 0.4958          | 0.8540   | 0.8529    | 0.8540 | 0.8523 |
| 0.2649        | 17.98 | 562  | 0.4927          | 0.8579   | 0.8570    | 0.8579 | 0.8562 |
| 0.2553        | 18.98 | 593  | 0.5095          | 0.8495   | 0.8473    | 0.8495 | 0.8474 |
| 0.2453        | 20.0  | 625  | 0.5162          | 0.8495   | 0.8467    | 0.8495 | 0.8467 |
| 0.2417        | 20.99 | 656  | 0.5375          | 0.8579   | 0.8573    | 0.8579 | 0.8543 |
| 0.241         | 21.98 | 687  | 0.5129          | 0.8568   | 0.8546    | 0.8568 | 0.8547 |
| 0.2257        | 22.98 | 718  | 0.5316          | 0.8596   | 0.8584    | 0.8596 | 0.8571 |
| 0.2087        | 24.0  | 750  | 0.5530          | 0.8512   | 0.8497    | 0.8512 | 0.8489 |
| 0.2196        | 24.99 | 781  | 0.5422          | 0.8613   | 0.8600    | 0.8613 | 0.8596 |
| 0.1975        | 25.98 | 812  | 0.5672          | 0.8529   | 0.8534    | 0.8529 | 0.8508 |
| 0.2135        | 26.98 | 843  | 0.5697          | 0.8523   | 0.8513    | 0.8523 | 0.8509 |
| 0.1946        | 28.0  | 875  | 0.5598          | 0.8557   | 0.8542    | 0.8557 | 0.8536 |
| 0.2006        | 28.99 | 906  | 0.5582          | 0.8591   | 0.8566    | 0.8591 | 0.8560 |
| 0.1968        | 29.76 | 930  | 0.5571          | 0.8591   | 0.8571    | 0.8591 | 0.8564 |


### Framework versions

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