🧠 MobileViT-Small β€” Brain Tumor Classifier (LoRA Fine-tune)

This model is a LoRA fine-tuned version of apple/mobilevit-small
for brain tumor classification on MRI images from the BRISC2025 dataset.


🧩 Configuration

Attribute Value
Base Model apple/mobilevit-small
Fine-tuning Method LoRA (Low-Rank Adaptation)
Dataset BRISC2025
Classes Glioma, Meningioma, No Tumor, Pituitary
Epochs 10
Batch Size 32
Learning Rate 0.0005
Optimizer AdamW
LoRA Config r=4, Ξ±=32, dropout=0.1, target_modules=[query, value]
Trainable Params 30.9K / 4.97M (0.62%)

🧠 Example Image

Brain Tumor Example


πŸ“Š Evaluation Results

Metric Avg Glioma Meningioma No Tumor Pituitary
Accuracy 0.9797 0.9750 0.9578 0.9969 0.9797
Precision 0.9570 0.9708 0.9419 0.9839 0.9316
Recall 0.9570 0.9379 0.8902 1.0000 1.0000
F1 Score 0.9565 0.9540 0.9154 0.9919 0.9646
AUC 0.9980 0.9980 0.9943 0.9999 0.9999

Test loss: 0.1146  Inference time: 0.436 s

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