Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision (ppv)	Recall (sensitivity)	Specificity	Npv	Auc
0.6624	6.25	100	0.5548	0.8235	0.7692	0.8333	0.7143	0.9	0.8182	0.8071
0.5201	12.49	200	0.4617	0.8824	0.8571	0.8571	0.8571	0.9	0.9	0.8786
0.5172	18.74	300	0.4249	0.8235	0.8000	0.75	0.8571	0.8	0.8889	0.8286
0.4605	24.98	400	0.3172	0.8235	0.7692	0.8333	0.7143	0.9	0.8182	0.8071
0.4894	31.25	500	0.4466	0.8235	0.7692	0.8333	0.7143	0.9	0.8182	0.8071
0.3694	37.49	600	0.5077	0.8235	0.7692	0.8333	0.7143	0.9	0.8182	0.8071
0.6172	43.74	700	0.5722	0.7647	0.7143	0.7143	0.7143	0.8	0.8	0.7571
0.3671	49.98	800	0.7006	0.7647	0.6667	0.8	0.5714	0.9	0.75	0.7357
0.4109	56.25	900	0.4410	0.8235	0.7692	0.8333	0.7143	0.9	0.8182	0.8071
0.3198	62.49	1000	0.7226	0.8235	0.7692	0.8333	0.7143	0.9	0.8182	0.8071
0.4283	68.74	1100	0.8089	0.8235	0.7692	0.8333	0.7143	0.9	0.8182	0.8071
0.3273	74.98	1200	0.9059	0.7647	0.6667	0.8	0.5714	0.9	0.75	0.7357
0.3237	81.25	1300	0.8520	0.8235	0.7692	0.8333	0.7143	0.9	0.8182	0.8071
0.2014	87.49	1400	0.9183	0.7647	0.6667	0.8	0.5714	0.9	0.75	0.7357
0.3204	93.74	1500	0.6769	0.8824	0.8571	0.8571	0.8571	0.9	0.9	0.8786
0.1786	99.98	1600	0.8748	0.8824	0.8571	0.8571	0.8571	0.9	0.9	0.8786

sergiocannata/dit-base-finetuned-brs

dit-base-finetuned-brs