---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
datasets:
- generator
metrics:
- accuracy
- f1
model-index:
- name: stool-condition-classification
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: stool-image
      type: generator
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8580527752502275
    - name: F1
      type: f1
      value: 0.8173302107728336
---

<!-- 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. -->

# stool-condition-classification

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 stool-image dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3669
- Auroc: 0.9121
- Accuracy: 0.8581
- Sensitivity: 0.7756
- Specificty: 0.9153
- F1: 0.8173

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Auroc  | Accuracy | Sensitivity | Specificty | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:-----------:|:----------:|:------:|
| 0.4071        | 0.98  | 100  | 0.4415          | 0.8876 | 0.8179   | 0.6629      | 0.9552     | 0.7738 |


### Framework versions

- Transformers 4.36.1
- Pytorch 2.0.1
- Datasets 2.15.0
- Tokenizers 0.15.0