---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: deit-tiny-patch16-224-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: 0.9117647058823529
---

<!-- 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. -->

# deit-tiny-patch16-224-finetuned-papsmear

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co./facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3421
- Accuracy: 0.9118

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.3521        | 0.9870  | 19   | 0.4595          | 0.8235   |
| 0.335         | 1.9740  | 38   | 0.4491          | 0.8603   |
| 0.3248        | 2.9610  | 57   | 0.4196          | 0.875    |
| 0.3271        | 4.0     | 77   | 0.5467          | 0.8015   |
| 0.3286        | 4.9870  | 96   | 0.4768          | 0.8162   |
| 0.2854        | 5.9740  | 115  | 0.4147          | 0.8676   |
| 0.2291        | 6.9610  | 134  | 0.4321          | 0.8676   |
| 0.2619        | 8.0     | 154  | 0.5726          | 0.8235   |
| 0.2196        | 8.9870  | 173  | 0.4344          | 0.8676   |
| 0.2116        | 9.9740  | 192  | 0.3809          | 0.875    |
| 0.1913        | 10.9610 | 211  | 0.3757          | 0.8603   |
| 0.1604        | 12.0    | 231  | 0.3551          | 0.8897   |
| 0.1307        | 12.9870 | 250  | 0.3330          | 0.8971   |
| 0.1425        | 13.9740 | 269  | 0.3421          | 0.9118   |
| 0.141         | 14.8052 | 285  | 0.3409          | 0.9118   |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1