FastQA implemented by Keras
This repository is implementation of FastQA proposed in this paper
- Python 3.6+
- TensorFlow, Keras, NumPy, spaCy
Building vocabulary
import os
import spacy
from data import Vocabulary, load_squad_tokens
PAD_TOKEN = '<pad>'
UNK_TOKEN = '<unk>'
if __name__ == '__main__':
train_file = '/path/to/train.txt'
vocab_file = 'vocab.pkl'
squad_tokens = load_squad_tokens(train_file)
token_to_index, index_to_token = Vocabulary.build(
squad_tokens, min_freq, max_size, (PAD_TOKEN, UNK_TOKEN), vocab_file)Training model
from models import FastQA
from data import SquadReader, Iterator, SquadConverter
from trainer import SquadTrainer
model = FastQA(vocab_size, embed_size, hidden_size).build()
model.compile(optimizer='adam', loss='sparse_categorical_crossentropy')
dataset = SquadReader(train_file)
converter = SquadConverter(token_to_index, '<pad>', '<unk>')
train_generator = Iterator(dataset, batch_size, converter)
trainer = SquadTrainer(model, train_generator, epoch)
trainer.run()$ git clone https://github.com/yasufumy/keras_fastqa.git| Model | F1 | Exact Match |
|---|---|---|
| BiLSTM / reported | 58.2 | 48.7 |
| BiLSTM / ours | 51.0 | 41.0 |
| FastQA* / reported | 74.9 | 65.5 |
| FastQA* / ours | 69.5 | 58.5 |