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tensorflowmachine-learningkerasdeep-learninglstm

Why accuracy stays zero in Keras LSTM while other metrics improve when training?

I have constructed a LSTM model for binary text classification problem. Here the labels are one hot encoded. Following is my constructed model

model = Sequential()
model.add(Embedding(input_dim=dictionary_length, output_dim=60, input_length=max_word_count))
model.add(LSTM(600))
model.add(Dense(units=max_word_count, activation='tanh', kernel_regularizer=regularizers.l2(0.04), activity_regularizer=regularizers.l2(0.015)))
model.add(Dense(units=max_word_count, activation='relu', kernel_regularizer=regularizers.l2(0.01), bias_regularizer=regularizers.l2(0.01)))
model.add(Dense(2, activation='softmax', kernel_regularizer=regularizers.l2(0.001)))

adam_optimizer = Adam(lr=0.001, decay=0.0001)
model.compile(loss='categorical_crossentropy', optimizer=adam_optimizer, 
              metrics=[tf.keras.metrics.Accuracy(), metrics.AUC(), metrics.Precision(), metrics.Recall()])

When I fit this model the accuracy stays 0 all the time but other matrices get improved. What is the issue here?

Epoch 1/3
94/94 [==============================] - 5s 26ms/step - loss: 3.4845 - accuracy: 0.0000e+00 - auc_4: 0.7583 - precision_4: 0.7251 - recall_4: 0.7251
Epoch 2/3
94/94 [==============================] - 2s 24ms/step - loss: 0.4772 - accuracy: 0.0000e+00 - auc_4: 0.9739 - precision_4: 0.9249 - recall_4: 0.9249
Epoch 3/3
94/94 [==============================] - 3s 27ms/step - loss: 0.1786 - accuracy: 0.0000e+00 - auc_4: 0.9985 - precision_4: 0.9860 - recall_4: 0.9860
Solution

  • Because you need CategoricalAccuracy : https://www.tensorflow.org/api_docs/python/tf/keras/metrics/CategoricalAccuracy to mesuring the accuracy of this problem.

    model.compile(loss='categorical_crossentropy', optimizer=adam_optimizer, 
              metrics=[tf.keras.metrics.CategoricalAccuracy(), metrics.AUC(), metrics.Precision(), metrics.Recall()])