CaMedBERT-512_fl32_checkpoint-17386

Model Card for Model ID

We fine-tuned our base model for 71 epochs on the Ca dataset, epoch 68 showed the best macro average f1 score on the evaluation dataset.

Metrics

eval_AVGf1 0.8032336746529752

eval_DIAGNOSIS.f1 0.7955801104972375

eval_DIAGNOSIS.precision 0.7656557699881843

eval_DIAGNOSIS.recall 0.82793867120954

eval_DIAGNOSTIC.f1 0.8097188097188096

eval_DIAGNOSTIC.precision 0.7797055730809674

eval_DIAGNOSTIC.recall 0.8421351504826803

eval_DRUG.f1 0.9214929214929215

eval_DRUG.precision 0.9002514668901928

eval_DRUG.recall 0.9437609841827768

eval_MEDICAL_FINDING.f1 0.7812833218340337

eval_MEDICAL_FINDING.precision 0.7604395604395604

eval_MEDICAL_FINDING.recall 0.8033019476331743

eval_THERAPY.f1 0.7080932097218742

eval_THERAPY.precision 0.6731777036684136

eval_THERAPY.recall 0.7468287526427061

eval_accuracy 0.9415681083480303

eval_f1 0.788057764075937

eval_loss 0.46635299921035767

eval_precision 0.7625447465929787

eval_recall 0.8153370937416062

eval_runtime 36.5944

eval_samples_per_second 223.586

eval_steps_per_second 27.955

test_AVGf1 0.765773820622575

test_DIAGNOSIS.f1 0.7267739575713241

test_DIAGNOSIS.precision 0.742803738317757

test_DIAGNOSIS.recall 0.711421410669531

test_DIAGNOSTIC.f1 0.7813144034806503

test_DIAGNOSTIC.precision 0.77124773960217

test_DIAGNOSTIC.recall 0.7916473317865429

test_DRUG.f1 0.9209993247805537

test_DRUG.precision 0.9021164021164021

test_DRUG.recall 0.9406896551724138

test_MEDICAL_FINDING.f1 0.7354366197183099

test_MEDICAL_FINDING.precision 0.6959164089988271

test_MEDICAL_FINDING.recall 0.7797156851033329

test_THERAPY.f1 0.6643447975620373

test_THERAPY.precision 0.6411764705882353

test_THERAPY.recall 0.6892502258355917

test_accuracy 0.9330358352068041

test_f1 0.7461369909791981

test_loss 0.5957663655281067

test_precision 0.7219958145170173

test_recall 0.7719484190072425

test_runtime 42.5823

test_samples_per_second 222.839

test_steps_per_second 27.875