Are you sure you want to delete this task? Once this task is deleted, it cannot be recovered.
|
|
6 years ago | |
|---|---|---|
| .. | ||
| Biaffine_parser | 6 years ago | |
| CNN-sentence_classification | 6 years ago | |
| Char-aware_NLM | 6 years ago | |
| Chinese_word_segmentation | 6 years ago | |
| HAN-document_classification | 7 years ago | |
| LSTM+self_attention_sentiment_analysis | 6 years ago | |
| POS_tagging | 6 years ago | |
| Star_transformer | 6 years ago | |
| seqence_labelling/Chinese_Word_Segmentation/data | 6 years ago | |
| README.md | 6 years ago | |
| __init__.py | 6 years ago | |
这里复现了在fastNLP中实现的模型,旨在达到与论文中相符的性能。
复现的模型有:
| 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 |
# 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)
一款轻量级的自然语言处理(NLP)工具包,目标是减少用户项目中的工程型代码,例如数据处理循环、训练循环、多卡运行等
Python Jupyter Notebook Text CSV Markdown