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}

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