---
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: 0.5038
- Accuracy: 0.8794
- Precision: 0.8781
- Recall: 0.8794
- F1: 0.8780

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.5123        | 0.99  | 62   | 1.2940          | 0.5276   | 0.5208    | 0.5276 | 0.5021 |
| 0.9691        | 2.0   | 125  | 0.7947          | 0.7272   | 0.7161    | 0.7272 | 0.7095 |
| 0.7326        | 2.99  | 187  | 0.5790          | 0.8010   | 0.7979    | 0.8010 | 0.7970 |
| 0.6346        | 4.0   | 250  | 0.6230          | 0.7931   | 0.7984    | 0.7931 | 0.7883 |
| 0.5945        | 4.99  | 312  | 0.5042          | 0.8360   | 0.8390    | 0.8360 | 0.8349 |
| 0.5607        | 6.0   | 375  | 0.4401          | 0.8455   | 0.8464    | 0.8455 | 0.8421 |
| 0.5137        | 6.99  | 437  | 0.4689          | 0.8506   | 0.8533    | 0.8506 | 0.8449 |
| 0.4842        | 8.0   | 500  | 0.4586          | 0.8484   | 0.8560    | 0.8484 | 0.8498 |
| 0.4816        | 8.99  | 562  | 0.4310          | 0.8534   | 0.8548    | 0.8534 | 0.8518 |
| 0.4538        | 10.0  | 625  | 0.4380          | 0.8529   | 0.8528    | 0.8529 | 0.8493 |
| 0.4334        | 10.99 | 687  | 0.4288          | 0.8625   | 0.8628    | 0.8625 | 0.8617 |
| 0.4086        | 12.0  | 750  | 0.4904          | 0.8608   | 0.8627    | 0.8608 | 0.8592 |
| 0.4143        | 12.99 | 812  | 0.4148          | 0.8675   | 0.8697    | 0.8675 | 0.8663 |
| 0.4164        | 14.0  | 875  | 0.4477          | 0.8647   | 0.8676    | 0.8647 | 0.8649 |
| 0.3464        | 14.99 | 937  | 0.4843          | 0.8512   | 0.8534    | 0.8512 | 0.8500 |
| 0.3654        | 16.0  | 1000 | 0.4632          | 0.8625   | 0.8631    | 0.8625 | 0.8619 |
| 0.2933        | 16.99 | 1062 | 0.4811          | 0.8596   | 0.8605    | 0.8596 | 0.8574 |
| 0.3299        | 18.0  | 1125 | 0.4574          | 0.8664   | 0.8664    | 0.8664 | 0.8656 |
| 0.3178        | 18.99 | 1187 | 0.4504          | 0.8703   | 0.8697    | 0.8703 | 0.8687 |
| 0.2976        | 20.0  | 1250 | 0.5002          | 0.8636   | 0.8619    | 0.8636 | 0.8610 |
| 0.2982        | 20.99 | 1312 | 0.4977          | 0.8720   | 0.8701    | 0.8720 | 0.8701 |
| 0.3092        | 22.0  | 1375 | 0.4820          | 0.8703   | 0.8710    | 0.8703 | 0.8687 |
| 0.2835        | 22.99 | 1437 | 0.4671          | 0.8715   | 0.8711    | 0.8715 | 0.8709 |
| 0.2596        | 24.0  | 1500 | 0.5075          | 0.8732   | 0.8737    | 0.8732 | 0.8729 |
| 0.2669        | 24.99 | 1562 | 0.4963          | 0.8732   | 0.8719    | 0.8732 | 0.8716 |
| 0.2409        | 26.0  | 1625 | 0.4955          | 0.8766   | 0.8749    | 0.8766 | 0.8754 |
| 0.2409        | 26.99 | 1687 | 0.4988          | 0.8777   | 0.8783    | 0.8777 | 0.8776 |
| 0.2683        | 28.0  | 1750 | 0.5038          | 0.8794   | 0.8781    | 0.8794 | 0.8780 |
| 0.2299        | 28.99 | 1812 | 0.5038          | 0.8771   | 0.8760    | 0.8771 | 0.8759 |
| 0.2394        | 29.76 | 1860 | 0.5048          | 0.8788   | 0.8779    | 0.8788 | 0.8775 |


### Framework versions

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