---
license: apache-2.0
base_model: facebook/convnextv2-large-1k-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: convnextv2-large-1k-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
should probably proofread and complete it, then remove this comment. -->

# convnextv2-large-1k-224-finetuned-Lesion-Classification-HAM10000-AH-60-20-20-Shuffled

This model is a fine-tuned version of [facebook/convnextv2-large-1k-224](https://huggingface.co/facebook/convnextv2-large-1k-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0946
- Accuracy: 0.9852

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9014        | 1.0   | 114  | 1.8872          | 0.3982   |
| 1.6303        | 2.0   | 229  | 1.6163          | 0.5928   |
| 1.291         | 3.0   | 343  | 1.2220          | 0.6773   |
| 1.0813        | 4.0   | 458  | 0.9574          | 0.7750   |
| 0.7168        | 5.0   | 572  | 0.7792          | 0.7603   |
| 0.6184        | 6.0   | 687  | 0.5539          | 0.8678   |
| 0.677         | 7.0   | 801  | 0.4482          | 0.8727   |
| 0.4876        | 8.0   | 916  | 0.3289          | 0.9269   |
| 0.4           | 9.0   | 1030 | 0.2379          | 0.9499   |
| 0.4122        | 10.0  | 1145 | 0.2452          | 0.9351   |
| 0.4494        | 11.0  | 1259 | 0.1790          | 0.9581   |
| 0.2026        | 11.95 | 1368 | 0.0946          | 0.9852   |


### Framework versions

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