---
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: 0.0721
- Accuracy: 0.9869

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8937        | 1.0   | 114  | 1.9040          | 0.3144   |
| 1.7208        | 2.0   | 229  | 1.6891          | 0.5632   |
| 1.3822        | 3.0   | 343  | 1.3554          | 0.6897   |
| 1.1497        | 4.0   | 458  | 1.2437          | 0.5755   |
| 0.8979        | 5.0   | 572  | 0.8548          | 0.7701   |
| 0.6382        | 6.0   | 687  | 0.6359          | 0.8424   |
| 0.583         | 7.0   | 801  | 0.4687          | 0.8966   |
| 0.6295        | 8.0   | 916  | 0.5029          | 0.8456   |
| 0.5367        | 9.0   | 1030 | 0.4742          | 0.8670   |
| 0.5091        | 10.0  | 1145 | 0.3038          | 0.9212   |
| 0.3521        | 11.0  | 1259 | 0.1855          | 0.9606   |
| 0.318         | 12.0  | 1374 | 0.1893          | 0.9573   |
| 0.2725        | 13.0  | 1488 | 0.2292          | 0.9409   |
| 0.2937        | 14.0  | 1603 | 0.0866          | 0.9836   |
| 0.1185        | 14.93 | 1710 | 0.0721          | 0.9869   |


### Framework versions

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