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ferrygun/ner_08.py

Last active June 11, 2020 01:15
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ner_08.py
input = Input(shape=(max_len,))
model = Embedding(input_dim=n_words, output_dim=50, input_length=max_len)(input)
model = Dropout(0.5)(model)
model = Bidirectional(LSTM(units=100, return_sequences=True, recurrent_dropout=0.1))(model)
out = TimeDistributed(Dense(n_tags, activation="softmax"))(model) # softmax output layer
model = Model(input, out)
opt = tf.keras.optimizers.Adam(lr=0.01, decay=1e-6)
model.compile(optimizer=opt, loss="categorical_crossentropy", metrics=["accuracy"])
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