---
library_name: transformers
license: apache-2.0
base_model: facebook/convnext-tiny-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-tiny-224-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: 0.8529411764705882
---

<!-- 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. -->

# convnext-tiny-224-finetuned-papsmear

This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4485
- Accuracy: 0.8529

## 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.4789        | 0.9935  | 38   | 1.4474          | 0.3235   |
| 1.2481        | 1.9869  | 76   | 1.0898          | 0.6397   |
| 0.9694        | 2.9804  | 114  | 0.9261          | 0.6471   |
| 0.8414        | 4.0     | 153  | 0.8016          | 0.7059   |
| 0.7675        | 4.9935  | 191  | 0.7258          | 0.7426   |
| 0.7131        | 5.9869  | 229  | 0.7147          | 0.7353   |
| 0.5973        | 6.9804  | 267  | 0.7040          | 0.7353   |
| 0.5543        | 8.0     | 306  | 0.6064          | 0.7941   |
| 0.4903        | 8.9935  | 344  | 0.5418          | 0.8382   |
| 0.3942        | 9.9869  | 382  | 0.5043          | 0.8456   |
| 0.3721        | 10.9804 | 420  | 0.4922          | 0.8456   |
| 0.4036        | 12.0    | 459  | 0.4944          | 0.8309   |
| 0.3444        | 12.9935 | 497  | 0.4760          | 0.8529   |
| 0.3385        | 13.9869 | 535  | 0.4597          | 0.8603   |
| 0.3161        | 14.9020 | 570  | 0.4485          | 0.8529   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1