Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	45	1.0375	0.4072	0.2743	0.3278	0.7192
No log	2.0	90	0.7673	0.4724	0.3914	0.4281	0.7522
No log	3.0	135	0.6973	0.4892	0.6637	0.5633	0.7757
No log	4.0	180	0.6645	0.5209	0.7237	0.6058	0.7961
No log	5.0	225	0.4692	0.6618	0.7041	0.6823	0.8644
No log	6.0	270	0.4469	0.6902	0.7552	0.7213	0.8776
No log	7.0	315	0.4761	0.6713	0.8123	0.7351	0.8745
No log	8.0	360	0.3956	0.7524	0.8063	0.7784	0.9055
No log	9.0	405	0.4272	0.7298	0.8332	0.7781	0.8976
No log	10.0	450	0.4285	0.7520	0.8577	0.8014	0.9096
No log	11.0	495	0.4022	0.7764	0.8693	0.8202	0.9147
0.4557	12.0	540	0.3584	0.8090	0.8640	0.8356	0.9287
0.4557	13.0	585	0.4022	0.8102	0.8733	0.8405	0.9253
0.4557	14.0	630	0.4149	0.8067	0.8902	0.8464	0.9268
0.4557	15.0	675	0.4160	0.8188	0.8919	0.8538	0.9290
0.4557	16.0	720	0.4015	0.8173	0.8932	0.8536	0.9302
0.4557	17.0	765	0.4084	0.8215	0.8945	0.8565	0.9309
0.4557	18.0	810	0.4133	0.8219	0.8955	0.8571	0.9307
0.4557	19.0	855	0.4131	0.8217	0.8955	0.8570	0.9310
0.4557	20.0	900	0.4130	0.8219	0.8955	0.8571	0.9310

ktgiahieu/deberta-v3-large-finetuned-ner

deberta-v3-large-finetuned-ner