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vit-base-patch16-224-in21k-lung_and_colon_histopathology
HumaP/vit-base-patch16-224-in21k-lung_and_colon_histopathology
vit-base-patch16-224-in21k-lung_and_colon_histopathology is a image classification model from HumaP. Use it when you need a label for an image. It is set up for transformers.
Google ViT model is finetuned on lung and colon histopathology image classification dataset. The dataset is available on Kaggle.
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At a glance
- Task
- Image Classification
- Library
- transformers
- Model type
- vit
- Access
- Public
- Created
- Dec 7, 2023
- Updated
- Dec 7, 2023
- SHA
- ed835639
Model card
From the Hugging Face model README
Description
Google ViT model is finetuned on lung and colon histopathology image classification dataset. The dataset is available on Kaggle.
About Dataset
It is a multiclass image classification dataset. This dataset contains 25,000 histopathological images with 5 classes.
There are five classes in the dataset, each with 5,000 images, being:
- Lung benign tissue
- Lung adenocarcinoma
- Lung squamous cell carcinoma
- Colon adenocarcinoma
- Colon benign tissue
Training Results
| Epoch | Training Loss | Training Accuracy | Validation Loss | Validation Accuracy |
|---|---|---|---|---|
| 1 | 0.2062 | 0.9760 | 0.0887 | 0.9948 |
| 2 | 0.0394 | 0.9990 | 0.0065 | 0.9986 |
| 3 | 0.0174 | 1.0 | 0.00507 | 0.9990 |
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- Created
- Dec 7, 2023
- Updated
- Dec 7, 2023