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Implementation of POS (part-of-speech) tagger with CNN and LSTM using PyTorch
Необходимо применять конволюцию к эмбеддингам символов, количество фильтров L
Сделать так, чтобы для каждого символа в слове генерился вектор x размерностью d_char из матрицы эмбеддингов для символов.
Необходимо сформировать вектор эмбеддингов для символов, который подается на вход CNN
Необходимо применить max-pooling, чтобы получить выходную размерность L для каждого слова
A small yet effective trick in the training phase is to sort the sentences on the number of words and then pad each sentence based on the longest sentence in the batch. This will speed up the training dramatically.
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