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efficientnetb0-brain-tumor-classification
linakosmina/efficientnetb0-brain-tumor-classification
efficientnetb0-brain-tumor-classification is a image classification model from linakosmina. Use it when you need a label for an image. It is set up for keras. The card lists the license as apache-2.0.
Model Description. This model is a fine-tuned EfficientNetB0 for classifying brain tumors from MRI scans. It was trained using transfer learning on a publicly available dataset from Kaggle. The model is capable of dis…
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At a glance
- Task
- Image Classification
- Library
- keras
- License
- apache-2.0
- Access
- Public
- Created
- Sep 13, 2025
- Updated
- Sep 13, 2025
- SHA
- ada72f8e
Base models
Model card
From the Hugging Face model README
Model Description. This model is a fine-tuned EfficientNetB0 for classifying brain tumors from MRI scans. It was trained using transfer learning on a publicly available dataset from Kaggle. The model is capable of distinguishing between four classes: pituitary, glioma, meningioma, and no_tumor.
Intended Use. This model is intended for non-commercial and research purposes only. It can be used for:
- Classifying brain tumors in MRI images.
- Serving as a baseline for further research.
Performance. The model was evaluated on a held-out test set and achieved the following results:
Metric Score Accuracy 99.31% Precision 99% Recall 99% F1-Score 99%
Training Data. The model was trained on the Brain Tumor MRI Dataset available on Kaggle.
Training Details
- Base Model: EfficientNetB0 (pre-trained on ImageNet)
- Framework: TensorFlow / Keras
- Training Platform: Google Colaboratory
- Task
- Image Classification
- Library
- keras
- License
- apache-2.0
- Created
- Sep 13, 2025
- Updated
- Sep 13, 2025