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Brain Tumour Dataset results

Loading best checkpoint: best_model.bson

============================================================
  FINAL TEST RESULTS
============================================================
  Test Loss     : 0.5022
  Test Accuracy : 0.9450 (94.5%)
============================================================

── Per-class Results ──────────────────────────────
Class           Precision    Recall        F1
──────────────────────────────────────────────────
glioma             0.991     0.818     0.896
meningioma         0.913     0.968     0.939
notumor            0.920     1.000     0.958
pituitary          0.968     0.995     0.982
──────────────────────────────────────────────────
Overall accuracy: 0.9450

── Confusion Matrix ───────────────────────────
      gli    men    not    pit    
gli     327     37     29      7  
men       3    387      4      6  
not       0      0    400      0  
pit       0      0      2    398  

Covid-19 dataset

============================================================
  FINAL TEST RESULTS
============================================================
  Test Loss     : 0.6089
  Test Accuracy : 0.8788 (87.9%)
============================================================

── Per-class Results ──────────────────────────────
Class           Precision    Recall        F1
──────────────────────────────────────────────────
Covid              1.000     1.000     1.000
Normal             0.929     0.650     0.765
Viral Pneumonia     0.731     0.950     0.826
──────────────────────────────────────────────────
Overall accuracy: 0.8788

── Confusion Matrix ───────────────────────────
      Cov    Nor    Vir    
Cov      26      0      0  
Nor       0     13      7  
Vir       0      1     19  
([26 0 0; 0 13 1; 0 7 19], 0.8787878787878788)

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Use Julia to run the notebook in Jupyter(IJulia) or use Colab

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