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.. | ||
datasets.py | ||
modules.py | ||
README.md | ||
run.sh | ||
train.py | ||
util.py |
Star-Transformer
paper: Star-Transformer
Performance (still in progress)
任务 | 数据集 | SOTA | 模型表现 |
---|---|---|---|
Pos Tagging | CTB 9.0 | - | ACC 92.31 |
Pos Tagging | CONLL 2012 | - | ACC 96.51 |
Named Entity Recognition | CONLL 2012 | - | F1 85.66 |
Text Classification | SST | - | 49.18 |
Natural Language Inference | SNLI | - | 83.76 |
Usage
# for sequence labeling(ner, pos tagging, etc)
from fastNLP.models.star_transformer import STSeqLabel
model = STSeqLabel(
vocab_size=10000, num_cls=50,
emb_dim=300)
# for sequence classification
from fastNLP.models.star_transformer import STSeqCls
model = STSeqCls(
vocab_size=10000, num_cls=50,
emb_dim=300)
# for natural language inference
from fastNLP.models.star_transformer import STNLICls
model = STNLICls(
vocab_size=10000, num_cls=50,
emb_dim=300)