---
library_name: transformers
license: apache-2.0
base_model: facebook/dinov2-small
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: dinov2-small-finetuned-papsmear
  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: 0.8602941176470589
---

<!-- 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. -->

# dinov2-small-finetuned-papsmear

This model is a fine-tuned version of [facebook/dinov2-small](https://huggingface.co/facebook/dinov2-small) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3843
- Accuracy: 0.8603

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.846         | 0.9935  | 38   | 1.0217          | 0.5956   |
| 1.0241        | 1.9869  | 76   | 0.8413          | 0.6544   |
| 0.9178        | 2.9804  | 114  | 0.7204          | 0.7426   |
| 0.693         | 4.0     | 153  | 0.5731          | 0.75     |
| 0.7157        | 4.9935  | 191  | 0.5501          | 0.8162   |
| 0.5006        | 5.9869  | 229  | 0.6096          | 0.7794   |
| 0.4576        | 6.9804  | 267  | 0.5535          | 0.7941   |
| 0.467         | 8.0     | 306  | 0.5041          | 0.8162   |
| 0.4378        | 8.9935  | 344  | 0.5771          | 0.8015   |
| 0.2876        | 9.9869  | 382  | 0.4234          | 0.8456   |
| 0.2308        | 10.9804 | 420  | 0.4946          | 0.8382   |
| 0.2312        | 12.0    | 459  | 0.5098          | 0.8309   |
| 0.1625        | 12.9935 | 497  | 0.3813          | 0.8603   |
| 0.1775        | 13.9869 | 535  | 0.3695          | 0.8529   |
| 0.1358        | 14.9020 | 570  | 0.3843          | 0.8603   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1