Tumor Detection ML Model
Model Description
This model is designed to classify brain tumor images using a Convolutional Neural Network (CNN). It has been trained and fine-tuned on a labeled dataset of brain tumor MRI images.
Training Details
- Framework: TensorFlow/Keras
- Optimizer: Adam with a learning rate scheduler
- Loss Function: Categorical Crossentropy
- Data Augmentation: Includes rotation, width/height shift, zoom, and horizontal flipping.
- Hyperparameter Tuning: Performed using Keras Tuner.
Metrics
The following metrics were used to evaluate the model's performance:
- Accuracy: Measures the overall correctness of predictions.
- F1 Score: Balances precision and recall.
- Precision: Indicates the proportion of true positives among positive predictions.
- Recall: Indicates the proportion of true positives among all actual positives.
Usage
You can load the model using the Hugging Face Transformers library:
from transformers import AutoModel
model = AutoModel.from_pretrained("YourUsername/Tumor_detection_ML_Model")
- Downloads last month
- 5
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.