---
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: 0.8088235294117647
---

<!-- 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: 0.4893
- Accuracy: 0.8088

## 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.706         | 0.9935  | 38   | 1.6028          | 0.2794   |
| 1.3867        | 1.9869  | 76   | 1.2961          | 0.4853   |
| 1.0784        | 2.9804  | 114  | 1.0588          | 0.5221   |
| 0.9128        | 4.0     | 153  | 0.8886          | 0.6618   |
| 0.7466        | 4.9935  | 191  | 0.8913          | 0.6029   |
| 0.6886        | 5.9869  | 229  | 0.7380          | 0.7059   |
| 0.6198        | 6.9804  | 267  | 0.7622          | 0.7132   |
| 0.6001        | 8.0     | 306  | 0.7083          | 0.6838   |
| 0.5542        | 8.9935  | 344  | 0.5909          | 0.7721   |
| 0.5161        | 9.9869  | 382  | 0.5909          | 0.7574   |
| 0.4631        | 10.9804 | 420  | 0.5677          | 0.7721   |
| 0.4284        | 12.0    | 459  | 0.5229          | 0.7868   |
| 0.4334        | 12.9935 | 497  | 0.5160          | 0.8015   |
| 0.4386        | 13.9869 | 535  | 0.4788          | 0.8015   |
| 0.3728        | 14.9020 | 570  | 0.4893          | 0.8088   |


### Framework versions

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