| epoch,train_precision,train_recall,train_f1,train_loss,val_precision,val_recall,val_f1,val_loss,model_name | |
| 0,0.7239382239382239,0.97911227154047,0.832408435072142,0.01817139005912299,0.6153846153846154,1.0,0.761904761904762,0.025600876120276422,dmis-lab/biobert-v1.1 | |
| 1,0.9512820512820512,0.9686684073107049,0.9598965071151357,0.004280440020540082,0.8,0.8,0.8000000000000002,0.014763055826133152,dmis-lab/biobert-v1.1 | |
| 2,1.0,0.9686684073107049,0.9840848806366048,0.0024200166264435876,0.9310344827586207,0.675,0.7826086956521738,0.026663977433136612,dmis-lab/biobert-v1.1 | |
| 3,1.0,0.9895561357702349,0.994750656167979,0.0009970445728253857,0.9310344827586207,0.675,0.7826086956521738,0.023675157960926025,dmis-lab/biobert-v1.1 | |
| 4,0.9973958333333334,1.0,0.998696219035202,0.00024732730325334907,0.7857142857142857,0.825,0.8048780487804876,0.02356158010222299,dmis-lab/biobert-v1.1 | |
| 5,1.0,1.0,1.0,0.00010623420357309322,0.8205128205128205,0.8,0.810126582278481,0.023674944550408132,dmis-lab/biobert-v1.1 | |
| 6,1.0,1.0,1.0,5.139963606143498e-05,0.9090909090909091,0.75,0.821917808219178,0.026155920379279687,dmis-lab/biobert-v1.1 | |
| 7,1.0,1.0,1.0,3.8080539161169135e-05,0.8611111111111112,0.775,0.8157894736842106,0.026953387733127148,dmis-lab/biobert-v1.1 | |
| 8,1.0,1.0,1.0,3.008640652806465e-05,0.8378378378378378,0.775,0.8051948051948051,0.027731853440248717,dmis-lab/biobert-v1.1 | |
| 9,1.0,1.0,1.0,2.463689066397747e-05,0.8378378378378378,0.775,0.8051948051948051,0.028430018061113033,dmis-lab/biobert-v1.1 | |