PassbyGrocer/resume_ner_herb

eval_p = 0.9822171390155553 eval_r = 0.9790383704405495 eval_f1 = 0.9806131065277388

train result

Epoch	Training Loss	Validation Loss	Precision	Recall	F1
1	No log	223.361084	0.980017	0.937134	0.957643
2	No log	61.423782	0.973549	0.959132	0.965962
3	2994.676800	72.477470	0.976213	0.962664	0.969052
4	2994.676800	103.387581	0.971125	0.962664	0.966845
5	33.797800	156.035553	0.975023	0.964581	0.969666
6	33.797800	265.293549	0.971879	0.969324	0.970583
7	20.226000	766.043457	0.974243	0.965187	0.969429
8	20.226000	1143.557495	0.974143	0.965691	0.969722
9	23.267200	996.235901	0.974592	0.968517	0.971405
10	23.267200	959.597229	0.974522	0.966398	0.970242

eval result

Label	Precision	Recall	F1-Score	Support
B-CONT	1.00	1.00	1.00	33
B-EDU	1.00	1.00	1.00	106
B-LOC	1.00	1.00	1.00	2
B-NAME	1.00	1.00	1.00	110
B-ORG	0.99	0.98	0.98	523
B-PRO	0.95	1.00	0.97	18
B-RACE	1.00	1.00	1.00	15
B-TITLE	0.96	0.96	0.96	690
I-CONT	1.00	1.00	1.00	97
I-EDU	1.00	1.00	1.00	283
I-LOC	1.00	1.00	1.00	8
I-NAME	1.00	1.00	1.00	177
I-ORG	0.99	0.98	0.99	4146
I-PRO	0.93	1.00	0.96	51
I-RACE	1.00	1.00	1.00	14
I-TITLE	0.97	0.97	0.97	2171
O	0.00	0.00	0.00	0

{'eval_loss': 684.596923828125, 'eval_precision': 0.9822171390155553, 'eval_recall': 0.9790383704405495, 'eval_f1': 0.9806131065277388, 'eval_runtime': 5.8637, 'eval_samples_per_second': 78.96, 'eval_steps_per_second': 4.946, 'epoch': 10.0}