PyTorch_Bert_Text_Classification
- Bert For Text Classification in SST
Requirement
PyTorch : 1.0.1
Python : 3.6
Cuda : 9.0 (support cuda speed up, can chose)
Usage
modify the config file, see the Config directory.
1、sh run_train_p.sh
2、python -u main.py --config ./Config/config.cfg --device cuda:0 --train -p
Bert
- use Bert_Script to extract feature from bert-base-uncased bert model.
Model
- CNN
- BiLSTM
- BiLSTM + BertFeature
- updating
Data
- SST-Binary
Result
The following test set accuracy are based on the best dev set accuracy.
| Model | Bert-Encoder | % SST-Binary |
|---|---|---|
| Bi-LSTM | - | 86.4360 |
| Bi-LSTM | AvgPooling | 86.3811 |
| Bi-LSTM | MaxPooling | 86.9303 |
| Bi-LSTM | BiLSTM+MaxPool | 89.7309 |
Reference
Question
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if you have any question, you can open a issue or email bamtercelboo@{gmail.com, 163.com}.
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if you have any good suggestions, you can PR or email me.