I am training an LSTM network but I have an error of
ValueError: logits and labels must have the same shape ((None, 10, 82) vs (None, 1))
I do not know where the error in the input shape is coming from. Any help would be highly appreciated. Thanks!
# The next step is to split training and testing data. For this we will use sklearn function train_test_split().
features_train, features_test, labels_train, labels_test = train_test_split(features, labels, test_size=0.2)
# features and labels shape
features_train = features_train.reshape(len(features_train), 1, features_train.shape[1])
features_train.shape
(180568, 1, 82)
model = Sequential()
model.add(LSTM(10, input_shape=(features_train.shape[1:])))
model.add(Embedding(180568, 82))
model.add(Dense(67, activation='softmax'))
model.add(Dropout(0.2))
model.add(Activation('sigmoid'))
model.build()
model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
model.summary()
Model: "sequential_3"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
lstm_3 (LSTM) (None, 10) 3720
_________________________________________________________________
embedding_3 (Embedding) (None, 10, 82) 14806576
_________________________________________________________________
dropout_3 (Dropout) (None, 10, 82) 0
_________________________________________________________________
activation_3 (Activation) (None, 10, 82) 0
=================================================================
Total params: 14,810,296
Trainable params: 14,810,296
Non-trainable params: 0
history = model.fit(features_train,
labels_train,
epochs=15,
batch_size=128,
validation_data=(features_test, labels_test))
与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…