---
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
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# beit-large-patch16-224-finetuned-Lesion-Classification-HAM10000-AH-60-20-20-Shuffled

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: 0.0487
- Accuracy: 0.9893

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1055        | 1.0   | 114  | 2.0091          | 0.1601   |
| 1.6582        | 2.0   | 229  | 1.5953          | 0.4187   |
| 1.2399        | 3.0   | 343  | 1.1053          | 0.5977   |
| 0.8417        | 4.0   | 458  | 0.7602          | 0.7241   |
| 0.5517        | 5.0   | 572  | 0.5651          | 0.8013   |
| 0.5777        | 6.0   | 687  | 0.3980          | 0.8768   |
| 0.408         | 7.0   | 801  | 0.2912          | 0.9154   |
| 0.2395        | 8.0   | 916  | 0.2185          | 0.9417   |
| 0.3613        | 9.0   | 1030 | 0.1753          | 0.9475   |
| 0.2408        | 10.0  | 1145 | 0.1353          | 0.9614   |
| 0.2777        | 11.0  | 1259 | 0.0699          | 0.9860   |
| 0.1528        | 11.95 | 1368 | 0.0487          | 0.9893   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3