---
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_g004
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train[:90]
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7777777777777778
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# urinary_carcinoma_classifier_g004

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: 0.5556
- Accuracy: 0.7778

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.8   | 1    | 0.6989          | 0.6111   |
| No log        | 1.6   | 2    | 0.6758          | 0.6111   |
| No log        | 2.4   | 3    | 0.6409          | 0.6667   |
| No log        | 4.0   | 5    | 0.6102          | 0.7222   |
| No log        | 4.8   | 6    | 0.6065          | 0.7778   |
| No log        | 5.6   | 7    | 0.6030          | 0.7778   |
| No log        | 6.4   | 8    | 0.6254          | 0.5556   |
| 0.6126        | 8.0   | 10   | 0.5948          | 0.7222   |
| 0.6126        | 8.8   | 11   | 0.5967          | 0.6667   |
| 0.6126        | 9.6   | 12   | 0.5784          | 0.7778   |
| 0.6126        | 10.4  | 13   | 0.5751          | 0.6667   |
| 0.6126        | 12.0  | 15   | 0.5556          | 0.7778   |


### Framework versions

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