---
library_name: transformers
license: apache-2.0
base_model: facebook/dinov2-base
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: ky-finetuned-skin
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9543516428392275
---

<!-- 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. -->

# ky-finetuned-skin

This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1260
- Accuracy: 0.9544

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.4572        | 1.0    | 281  | 0.7687          | 0.7524   |
| 0.7019        | 2.0    | 562  | 0.4615          | 0.8533   |
| 0.5125        | 3.0    | 843  | 0.3146          | 0.8942   |
| 0.4267        | 4.0    | 1124 | 0.2547          | 0.9180   |
| 0.3441        | 5.0    | 1405 | 0.2028          | 0.9333   |
| 0.3034        | 6.0    | 1686 | 0.1992          | 0.9320   |
| 0.2581        | 7.0    | 1967 | 0.1590          | 0.9453   |
| 0.2167        | 8.0    | 2248 | 0.1490          | 0.9468   |
| 0.1879        | 9.0    | 2529 | 0.1318          | 0.9541   |
| 0.16          | 9.9661 | 2800 | 0.1260          | 0.9544   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0