[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify the code snippets into categories from the provided list of categories. List of categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']"}, {'role': 'user', 'content': "Identify to which category the provided code belongs and assign the code snippet to at least 1 but up to 5 categories based on the probabilities, ignore if the probability of the category is negligible. Strictly provide your response as a list. Avoid providing any additional information, commentary, or personal opinions.\\nPython Code:EMBEDDING_DIM = 256\n\nmodel = Sequential()\nmodel.add(Embedding(vocabulary_size, EMBEDDING_DIM, input_length=row_max_length))\nmodel.add(SpatialDropout1D(0.2))\nmodel.add(Bidirectional(GRU(128)))\nmodel.add(Dense(128, activation='relu'))\nmodel.add(Dropout(0.2))\nmodel.add(Dense(target_length, activation='softmax'))\nmodel.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])\n\ncallback = tf.keras.callbacks.EarlyStopping(monitor='val_loss', patience=1)\nhistory = model.fit(X_train_pad, y_train_cat, epochs=5, validation_data=(X_test_pad, y_test_cat), batch_size=128, callbacks=[callback])"}, {'role': 'assistant', 'content': "['modelling']"}]