---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-in21k-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: 0.9338235294117647
---

<!-- 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. -->

# vit-base-patch16-224-in21k-finetuned-papsmear

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co./google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2870
- Accuracy: 0.9338

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log        | 0.9231  | 9    | 1.7879          | 0.2059   |
| 1.8037        | 1.9487  | 19   | 1.6485          | 0.4044   |
| 1.6961        | 2.9744  | 29   | 1.4882          | 0.3971   |
| 1.5407        | 4.0     | 39   | 1.3069          | 0.5221   |
| 1.3308        | 4.9231  | 48   | 1.1339          | 0.6029   |
| 1.1074        | 5.9487  | 58   | 0.9396          | 0.75     |
| 0.9162        | 6.9744  | 68   | 0.8551          | 0.7647   |
| 0.8174        | 8.0     | 78   | 0.8291          | 0.7574   |
| 0.7135        | 8.9231  | 87   | 0.7505          | 0.7941   |
| 0.6222        | 9.9487  | 97   | 0.6434          | 0.8456   |
| 0.5445        | 10.9744 | 107  | 0.5996          | 0.8529   |
| 0.4935        | 12.0    | 117  | 0.5514          | 0.8529   |
| 0.4131        | 12.9231 | 126  | 0.5029          | 0.8603   |
| 0.4012        | 13.9487 | 136  | 0.5566          | 0.8382   |
| 0.3689        | 14.9744 | 146  | 0.5533          | 0.8382   |
| 0.3533        | 16.0    | 156  | 0.4232          | 0.8971   |
| 0.2954        | 16.9231 | 165  | 0.4589          | 0.8897   |
| 0.2907        | 17.9487 | 175  | 0.4223          | 0.8971   |
| 0.2804        | 18.9744 | 185  | 0.4056          | 0.8971   |
| 0.2469        | 20.0    | 195  | 0.3904          | 0.9118   |
| 0.2643        | 20.9231 | 204  | 0.3866          | 0.9044   |
| 0.2212        | 21.9487 | 214  | 0.4173          | 0.875    |
| 0.2476        | 22.9744 | 224  | 0.6001          | 0.8015   |
| 0.2347        | 24.0    | 234  | 0.3900          | 0.9044   |
| 0.207         | 24.9231 | 243  | 0.4033          | 0.8897   |
| 0.1803        | 25.9487 | 253  | 0.3510          | 0.9265   |
| 0.1979        | 26.9744 | 263  | 0.3723          | 0.9191   |
| 0.1821        | 28.0    | 273  | 0.4320          | 0.8824   |
| 0.1992        | 28.9231 | 282  | 0.3557          | 0.9118   |
| 0.2154        | 29.9487 | 292  | 0.3362          | 0.9191   |
| 0.1801        | 30.9744 | 302  | 0.4358          | 0.875    |
| 0.1794        | 32.0    | 312  | 0.3500          | 0.9191   |
| 0.1566        | 32.9231 | 321  | 0.3046          | 0.9265   |
| 0.1432        | 33.9487 | 331  | 0.3239          | 0.9265   |
| 0.145         | 34.9744 | 341  | 0.3311          | 0.9338   |
| 0.1578        | 36.0    | 351  | 0.3029          | 0.9338   |
| 0.1511        | 36.9231 | 360  | 0.3010          | 0.9338   |
| 0.139         | 37.9487 | 370  | 0.2982          | 0.9265   |
| 0.1294        | 38.9744 | 380  | 0.3261          | 0.9191   |
| 0.1263        | 40.0    | 390  | 0.2932          | 0.9338   |
| 0.1263        | 40.9231 | 399  | 0.2944          | 0.9338   |
| 0.1216        | 41.9487 | 409  | 0.2867          | 0.9338   |
| 0.1199        | 42.9744 | 419  | 0.2887          | 0.9338   |
| 0.128         | 44.0    | 429  | 0.2825          | 0.9338   |
| 0.1115        | 44.9231 | 438  | 0.2880          | 0.9338   |
| 0.1179        | 45.9487 | 448  | 0.2871          | 0.9338   |
| 0.12          | 46.1538 | 450  | 0.2870          | 0.9338   |


### Framework versions

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