---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: urinary_carcinoma_classifier_g001
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train[:23]
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6
---

<!-- 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. -->

# urinary_carcinoma_classifier_g001

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: 0.6827
- Accuracy: 0.6

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1    | 0.7147          | 0.4      |
| No log        | 2.0   | 2    | 0.7114          | 0.4      |
| No log        | 3.0   | 3    | 0.6968          | 0.2      |
| No log        | 4.0   | 4    | 0.7055          | 0.4      |
| No log        | 5.0   | 5    | 0.6741          | 0.4      |
| No log        | 6.0   | 6    | 0.6580          | 0.6      |
| No log        | 7.0   | 7    | 0.6092          | 0.6      |
| No log        | 8.0   | 8    | 0.6200          | 0.6      |
| No log        | 9.0   | 9    | 0.6139          | 0.6      |
| 0.3094        | 10.0  | 10   | 0.5969          | 0.6      |
| 0.3094        | 11.0  | 11   | 0.5677          | 0.6      |
| 0.3094        | 12.0  | 12   | 0.6021          | 0.6      |
| 0.3094        | 13.0  | 13   | 0.6189          | 0.6      |
| 0.3094        | 14.0  | 14   | 0.6054          | 0.6      |
| 0.3094        | 15.0  | 15   | 0.6240          | 0.6      |
| 0.3094        | 16.0  | 16   | 0.5388          | 0.6      |
| 0.3094        | 17.0  | 17   | 0.5320          | 0.6      |
| 0.3094        | 18.0  | 18   | 0.5973          | 0.6      |
| 0.3094        | 19.0  | 19   | 0.5981          | 0.8      |
| 0.1723        | 20.0  | 20   | 0.6531          | 0.6      |
| 0.1723        | 21.0  | 21   | 0.6246          | 0.6      |
| 0.1723        | 22.0  | 22   | 0.6718          | 0.6      |
| 0.1723        | 23.0  | 23   | 0.6692          | 0.6      |
| 0.1723        | 24.0  | 24   | 0.6537          | 0.6      |
| 0.1723        | 25.0  | 25   | 0.4650          | 0.6      |
| 0.1723        | 26.0  | 26   | 0.6873          | 0.6      |
| 0.1723        | 27.0  | 27   | 0.6461          | 0.6      |
| 0.1723        | 28.0  | 28   | 0.5876          | 0.8      |
| 0.1723        | 29.0  | 29   | 0.4898          | 0.6      |
| 0.1049        | 30.0  | 30   | 0.6827          | 0.6      |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1
- Datasets 2.20.0
- Tokenizers 0.19.1