---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: beit-large-patch16-224-finetuned-Lesion-Classification-HAM10000-AH-60-20-20
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: Augmented-Final
      split: train
      args: Augmented-Final
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9907502569373073
---

<!-- 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-finetuned-Lesion-Classification-HAM10000-AH-60-20-20

This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0434
- Accuracy: 0.9908

## 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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.9
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9688        | 1.0   | 122  | 1.8425          | 0.2775   |
| 1.4822        | 2.0   | 244  | 1.3833          | 0.5457   |
| 1.1239        | 3.0   | 366  | 0.9321          | 0.6680   |
| 0.8686        | 4.0   | 488  | 0.6691          | 0.7698   |
| 0.5234        | 5.0   | 610  | 0.4872          | 0.8335   |
| 0.5246        | 6.0   | 732  | 0.3586          | 0.8736   |
| 0.3691        | 7.0   | 854  | 0.3134          | 0.8993   |
| 0.4708        | 8.0   | 976  | 0.2069          | 0.9394   |
| 0.1694        | 9.0   | 1098 | 0.1832          | 0.9414   |
| 0.2749        | 10.0  | 1220 | 0.1198          | 0.9640   |
| 0.1777        | 11.0  | 1342 | 0.0845          | 0.9733   |
| 0.1529        | 12.0  | 1464 | 0.0434          | 0.9908   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3