A Biomedical Pos-Tagger for English
Trained with the GENIA corpus.
Eval:
precision recall f1-score support
0 0.98 1.00 0.99 263
3 0.93 1.00 0.97 14
5 1.00 1.00 1.00 8
6 0.99 0.99 0.99 169
7 1.00 1.00 1.00 203
8 0.99 1.00 1.00 195
9 0.95 0.78 0.85 98
10 0.83 1.00 0.91 5
11 0.96 0.97 0.96 532
12 1.00 1.00 1.00 252
13 0.99 0.98 0.99 1575
14 0.95 0.95 0.95 133
15 0.89 0.89 0.89 9
16 1.00 1.00 1.00 3
18 0.99 1.00 0.99 69
19 1.00 0.95 0.98 22
20 0.99 1.00 1.00 395
22 1.00 1.00 1.00 1328
23 1.00 1.00 1.00 987
24 1.00 1.00 1.00 6
25 0.00 0.00 0.00 0
26 1.00 1.00 1.00 620
27 0.00 0.00 0.00 1
28 1.00 1.00 1.00 39
29 0.98 0.99 0.98 5674
30 0.97 0.96 0.96 2075
31 1.00 0.71 0.83 7
32 1.00 0.80 0.89 5
33 1.00 1.00 1.00 58
34 1.00 1.00 1.00 2
35 0.96 0.96 0.96 336
37 0.99 1.00 1.00 1579
38 1.00 1.00 1.00 1446
39 1.00 0.98 0.99 57
accuracy 0.99 18165
macro avg 0.92 0.91 0.91 18165
weighted avg 0.99 0.99 0.99 18165
F1: 0.985267446136761 Accuracy: 0.9853564547206166
Tags:
{0: 'VBD',
1: 'N',
2: 'XT',
3: 'JJS',
4: 'E2A',
5: 'WRB',
6: 'VB',
7: 'TO',
8: 'VBP',
9: 'FW',
10: 'EX',
11: 'VBN',
12: 'VBZ',
13: 'NNS',
14: 'VBG',
15: 'RBR',
16: 'WP',
17: 'CT',
18: 'PRP',
19: 'JJR',
20: 'CC',
21: 'NNPS',
22: 'CD',
23: 'DT',
24: 'NNP',
25: 'PDT',
26: 'LS',
27: 'PP',
28: 'PRP$',
29: 'NN',
30: 'JJ',
31: 'RP',
32: 'RBS',
33: 'MD',
34: 'WP$',
35: 'RB',
36: 'SYM',
37: 'IN',
38: 'PUNCT',
39: 'WDT',
40: 'POS',
41: '<pad>'}
Parameters:
nepochs = 30 (stop at 18th)
batch_size = 32
batch_status = 32
learning_rate = 1e-5
early_stop = 3
max_length = 200
checkpoint: dmis-lab/biobert-base-cased-v1.2
See more in: https://github.com/lisaterumi/postagger-bio-english
