---
license: apache-2.0
base_model: microsoft/beit-large-patch16-224-pt22k
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: beit-large-patch16-224-pt22k-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. -->

# beit-large-patch16-224-pt22k-finetuned-galaxy10-decals

This model is a fine-tuned version of [microsoft/beit-large-patch16-224-pt22k](https://huggingface.co/microsoft/beit-large-patch16-224-pt22k) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5047
- Accuracy: 0.8771
- Precision: 0.8770
- Recall: 0.8771
- F1: 0.8764

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.5632        | 0.99  | 62   | 1.3358          | 0.5265   | 0.5377    | 0.5265 | 0.4840 |
| 0.8801        | 2.0   | 125  | 0.7053          | 0.7717   | 0.7710    | 0.7717 | 0.7559 |
| 0.7408        | 2.99  | 187  | 0.5995          | 0.7897   | 0.7878    | 0.7897 | 0.7803 |
| 0.6124        | 4.0   | 250  | 0.5448          | 0.8140   | 0.8178    | 0.8140 | 0.8076 |
| 0.5799        | 4.99  | 312  | 0.5354          | 0.8174   | 0.8224    | 0.8174 | 0.8165 |
| 0.567         | 6.0   | 375  | 0.5044          | 0.8247   | 0.8314    | 0.8247 | 0.8194 |
| 0.5237        | 6.99  | 437  | 0.4913          | 0.8388   | 0.8429    | 0.8388 | 0.8371 |
| 0.4674        | 8.0   | 500  | 0.4927          | 0.8484   | 0.8541    | 0.8484 | 0.8477 |
| 0.4869        | 8.99  | 562  | 0.4167          | 0.8546   | 0.8570    | 0.8546 | 0.8526 |
| 0.4442        | 10.0  | 625  | 0.4086          | 0.8579   | 0.8583    | 0.8579 | 0.8564 |
| 0.4294        | 10.99 | 687  | 0.4743          | 0.8489   | 0.8516    | 0.8489 | 0.8489 |
| 0.4032        | 12.0  | 750  | 0.4350          | 0.8664   | 0.8651    | 0.8664 | 0.8647 |
| 0.4028        | 12.99 | 812  | 0.4443          | 0.8568   | 0.8623    | 0.8568 | 0.8561 |
| 0.3939        | 14.0  | 875  | 0.4193          | 0.8608   | 0.8605    | 0.8608 | 0.8593 |
| 0.3447        | 14.99 | 937  | 0.4289          | 0.8698   | 0.8692    | 0.8698 | 0.8688 |
| 0.354         | 16.0  | 1000 | 0.4471          | 0.8653   | 0.8661    | 0.8653 | 0.8648 |
| 0.2934        | 16.99 | 1062 | 0.4888          | 0.8574   | 0.8573    | 0.8574 | 0.8546 |
| 0.3262        | 18.0  | 1125 | 0.4605          | 0.8602   | 0.8602    | 0.8602 | 0.8588 |
| 0.3287        | 18.99 | 1187 | 0.4439          | 0.8681   | 0.8682    | 0.8681 | 0.8673 |
| 0.2848        | 20.0  | 1250 | 0.4986          | 0.8641   | 0.8633    | 0.8641 | 0.8615 |
| 0.283         | 20.99 | 1312 | 0.4663          | 0.8692   | 0.8681    | 0.8692 | 0.8676 |
| 0.3106        | 22.0  | 1375 | 0.4668          | 0.8720   | 0.8735    | 0.8720 | 0.8697 |
| 0.2785        | 22.99 | 1437 | 0.4899          | 0.8664   | 0.8649    | 0.8664 | 0.8650 |
| 0.2635        | 24.0  | 1500 | 0.5047          | 0.8771   | 0.8770    | 0.8771 | 0.8764 |
| 0.2573        | 24.99 | 1562 | 0.5144          | 0.8732   | 0.8730    | 0.8732 | 0.8723 |
| 0.238         | 26.0  | 1625 | 0.5012          | 0.8732   | 0.8729    | 0.8732 | 0.8723 |
| 0.2358        | 26.99 | 1687 | 0.5021          | 0.8681   | 0.8709    | 0.8681 | 0.8690 |
| 0.2624        | 28.0  | 1750 | 0.5154          | 0.8715   | 0.8711    | 0.8715 | 0.8705 |
| 0.229         | 28.99 | 1812 | 0.5087          | 0.8698   | 0.8690    | 0.8698 | 0.8689 |
| 0.227         | 29.76 | 1860 | 0.5104          | 0.8726   | 0.8725    | 0.8726 | 0.8718 |


### Framework versions

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