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---
license: apache-2.0
tags:
- generated_from_keras_callback
- vision_transformer
model-index:
- name: Guldeniz/vit-base-patch16-224-in21k-lung_and_colon
results: []
language:
- en
metrics:
- accuracy
library_name: transformers
pipeline_tag: image-classification
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# Guldeniz/vit-base-patch16-224-in21k-lung_and_colon
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on Lung and Colon Histopathological Images dataset. This dataset can be reach via [Kaggle](https://www.kaggle.com/datasets/andrewmvd/lung-and-colon-cancer-histopathological-images).
It achieves the following results on the evaluation set:
- Train Loss: 0.0088
- Train Accuracy: 1.0
- Train Top-3-accuracy: 1.0
- Validation Loss: 0.0084
- Validation Accuracy: 0.9997
- Validation Top-3-accuracy: 1.0
- Epoch: 3
## Model description
The vision transformer model, trained by Google, has been fine-tuned using a lung and colon cancer image dataset consisting of a total of 25,000 images across 5 labels. The obtained results are highly promising, and the model demonstrates the ability to predict the following listed labels.
- colon_aca
- colon_n
- lung_aca
- lung_n
- lung_scc
### Training hyperparameters
The following hyperparameters were used during training:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 3325, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
### Training results
| Train Loss | Train Accuracy | Train Top-3-accuracy | Validation Loss | Validation Accuracy | Validation Top-3-accuracy | Epoch |
|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:|
| 0.1870 | 0.9784 | 0.9985 | 0.0455 | 0.9987 | 1.0 | 0 |
| 0.0345 | 0.9972 | 1.0 | 0.0189 | 0.9995 | 1.0 | 1 |
| 0.0134 | 1.0 | 1.0 | 0.0110 | 0.9997 | 1.0 | 2 |
| 0.0088 | 1.0 | 1.0 | 0.0084 | 0.9997 | 1.0 | 3 |
### Framework versions
- Transformers 4.26.1
- TensorFlow 2.12.0
- Datasets 2.10.1
- Tokenizers 0.13.3 |