---
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[:34]
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8571428571428571
---

<!-- 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: 0.1765
- Accuracy: 0.8571

## 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1    | 0.6758          | 0.5714   |
| No log        | 2.0   | 2    | 0.6747          | 0.5714   |
| No log        | 3.0   | 3    | 0.6558          | 0.5714   |
| No log        | 4.0   | 4    | 0.6576          | 0.5714   |
| No log        | 5.0   | 5    | 0.6297          | 0.5714   |
| No log        | 6.0   | 6    | 0.6131          | 0.5714   |
| No log        | 7.0   | 7    | 0.5552          | 0.5714   |
| No log        | 8.0   | 8    | 0.5017          | 0.7143   |
| No log        | 9.0   | 9    | 0.4695          | 0.8571   |
| 0.2846        | 10.0  | 10   | 0.4277          | 0.8571   |
| 0.2846        | 11.0  | 11   | 0.4228          | 0.8571   |
| 0.2846        | 12.0  | 12   | 0.4115          | 0.8571   |
| 0.2846        | 13.0  | 13   | 0.3575          | 1.0      |
| 0.2846        | 14.0  | 14   | 0.4240          | 0.8571   |
| 0.2846        | 15.0  | 15   | 0.3832          | 1.0      |
| 0.2846        | 16.0  | 16   | 0.3363          | 1.0      |
| 0.2846        | 17.0  | 17   | 0.3375          | 0.8571   |
| 0.2846        | 18.0  | 18   | 0.3222          | 1.0      |
| 0.2846        | 19.0  | 19   | 0.2372          | 1.0      |
| 0.141         | 20.0  | 20   | 0.2795          | 1.0      |
| 0.141         | 21.0  | 21   | 0.2726          | 1.0      |
| 0.141         | 22.0  | 22   | 0.2010          | 1.0      |
| 0.141         | 23.0  | 23   | 0.1791          | 1.0      |
| 0.141         | 24.0  | 24   | 0.1794          | 1.0      |
| 0.141         | 25.0  | 25   | 0.2308          | 1.0      |
| 0.141         | 26.0  | 26   | 0.1686          | 1.0      |
| 0.141         | 27.0  | 27   | 0.2678          | 0.8571   |
| 0.141         | 28.0  | 28   | 0.3142          | 0.8571   |
| 0.141         | 29.0  | 29   | 0.1509          | 1.0      |
| 0.072         | 30.0  | 30   | 0.1522          | 1.0      |
| 0.072         | 31.0  | 31   | 0.1862          | 1.0      |
| 0.072         | 32.0  | 32   | 0.1927          | 1.0      |
| 0.072         | 33.0  | 33   | 0.1600          | 1.0      |
| 0.072         | 34.0  | 34   | 0.1520          | 1.0      |
| 0.072         | 35.0  | 35   | 0.1377          | 1.0      |
| 0.072         | 36.0  | 36   | 0.2727          | 0.8571   |
| 0.072         | 37.0  | 37   | 0.1470          | 1.0      |
| 0.072         | 38.0  | 38   | 0.2727          | 0.8571   |
| 0.072         | 39.0  | 39   | 0.2244          | 0.8571   |
| 0.0444        | 40.0  | 40   | 0.1122          | 1.0      |
| 0.0444        | 41.0  | 41   | 0.2727          | 0.8571   |
| 0.0444        | 42.0  | 42   | 0.2733          | 0.8571   |
| 0.0444        | 43.0  | 43   | 0.2109          | 0.8571   |
| 0.0444        | 44.0  | 44   | 0.3147          | 0.8571   |
| 0.0444        | 45.0  | 45   | 0.3256          | 0.8571   |
| 0.0444        | 46.0  | 46   | 0.2474          | 0.8571   |
| 0.0444        | 47.0  | 47   | 0.2670          | 0.8571   |
| 0.0444        | 48.0  | 48   | 0.2003          | 0.8571   |
| 0.0444        | 49.0  | 49   | 0.2966          | 0.8571   |
| 0.0361        | 50.0  | 50   | 0.1765          | 0.8571   |


### Framework versions

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