---
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: beit-large-patch16-224-finetuned-Lesion-Classification-HAM10000-AH-60-20-20-Shuffled-3rd
  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-finetuned-Lesion-Classification-HAM10000-AH-60-20-20-Shuffled-3rd

This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0488
- Accuracy: 0.9901

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9835        | 1.0   | 114  | 1.9296          | 0.2315   |
| 1.6045        | 2.0   | 229  | 1.4334          | 0.5172   |
| 1.0525        | 3.0   | 343  | 0.9298          | 0.6962   |
| 0.795         | 4.0   | 458  | 0.6580          | 0.7709   |
| 0.5739        | 5.0   | 572  | 0.4717          | 0.8366   |
| 0.5821        | 6.0   | 687  | 0.3511          | 0.8851   |
| 0.4566        | 7.0   | 801  | 0.2705          | 0.9204   |
| 0.2751        | 8.0   | 916  | 0.2114          | 0.9384   |
| 0.2352        | 9.0   | 1030 | 0.1303          | 0.9688   |
| 0.1831        | 10.0  | 1145 | 0.1194          | 0.9688   |
| 0.1515        | 11.0  | 1259 | 0.0673          | 0.9869   |
| 0.204         | 11.95 | 1368 | 0.0488          | 0.9901   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3