End-to-End Non-Factoid Question Answering with an Interactive Visualization of Neural Attention Weights
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چکیده
1 data -module: data.insuranceqa.v2 2 model -module: model.ap_lstm 3 training -module: training.dynamic 4 evaluation -module: evaluation.default 5 6 data: 7 embeddings: data/glove.6B.100d.txt 8 insuranceqa: data/insuranceQA 9 lowercased: true 10 .. 11 12 model: 13 lstm_cell_size: 141 14 margin: 0.2 15 trainable_embeddings: true 16 .. 17 18 training: 19 batchsize: 20 20 epochs: 100 21 save_folder: checkpoints/ap_lstm 22 dropout: 0.3 23 optimizer: adam 24 initial_learning_rate: 0.001 25 scorer: accuracy 26 .. 27 28 evaluation: 29 skip: true
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تاریخ انتشار 2017