Datasets:
HenryAI
/
KerasBERTv1-Data

Dataset card Data Studio Files Community
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model = build_model((SAMPLING_RATE // 2, 1), len(class_names))
model.summary()
# Compile the model using Adam's default learning rate
model.compile(
optimizer=\"Adam\", loss=\"sparse_categorical_crossentropy\", metrics=[\"accuracy\"]
)
# Add callbacks:
# 'EarlyStopping' to stop training when the model is not enhancing anymore
# 'ModelCheckPoint' to always keep the model that has the best val_accuracy
model_save_filename = \"model.h5\"
earlystopping_cb = keras.callbacks.EarlyStopping(patience=10, restore_best_weights=True)
mdlcheckpoint_cb = keras.callbacks.ModelCheckpoint(
model_save_filename, monitor=\"val_accuracy\", save_best_only=True
)
Model: \"model\"
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input (InputLayer) [(None, 8000, 1)] 0
__________________________________________________________________________________________________
conv1d_1 (Conv1D) (None, 8000, 16) 64 input[0][0]
__________________________________________________________________________________________________
activation (Activation) (None, 8000, 16) 0 conv1d_1[0][0]
__________________________________________________________________________________________________
conv1d_2 (Conv1D) (None, 8000, 16) 784 activation[0][0]
__________________________________________________________________________________________________
conv1d (Conv1D) (None, 8000, 16) 32 input[0][0]
__________________________________________________________________________________________________
add (Add) (None, 8000, 16) 0 conv1d_2[0][0]
conv1d[0][0]
__________________________________________________________________________________________________
activation_1 (Activation) (None, 8000, 16) 0 add[0][0]
__________________________________________________________________________________________________
max_pooling1d (MaxPooling1D) (None, 4000, 16) 0 activation_1[0][0]
__________________________________________________________________________________________________
conv1d_4 (Conv1D) (None, 4000, 32) 1568 max_pooling1d[0][0]
__________________________________________________________________________________________________
activation_2 (Activation) (None, 4000, 32) 0 conv1d_4[0][0]
__________________________________________________________________________________________________
conv1d_5 (Conv1D) (None, 4000, 32) 3104 activation_2[0][0]
__________________________________________________________________________________________________
conv1d_3 (Conv1D) (None, 4000, 32) 544 max_pooling1d[0][0]
__________________________________________________________________________________________________
add_1 (Add) (None, 4000, 32) 0 conv1d_5[0][0]
conv1d_3[0][0]
__________________________________________________________________________________________________
activation_3 (Activation) (None, 4000, 32) 0 add_1[0][0]
__________________________________________________________________________________________________
max_pooling1d_1 (MaxPooling1D) (None, 2000, 32) 0 activation_3[0][0]
__________________________________________________________________________________________________
conv1d_7 (Conv1D) (None, 2000, 64) 6208 max_pooling1d_1[0][0]
__________________________________________________________________________________________________
activation_4 (Activation) (None, 2000, 64) 0 conv1d_7[0][0]
__________________________________________________________________________________________________
conv1d_8 (Conv1D) (None, 2000, 64) 12352 activation_4[0][0]
__________________________________________________________________________________________________
activation_5 (Activation) (None, 2000, 64) 0 conv1d_8[0][0]
__________________________________________________________________________________________________
conv1d_9 (Conv1D) (None, 2000, 64) 12352 activation_5[0][0]
__________________________________________________________________________________________________
conv1d_6 (Conv1D) (None, 2000, 64) 2112 max_pooling1d_1[0][0]
__________________________________________________________________________________________________
add_2 (Add) (None, 2000, 64) 0 conv1d_9[0][0]
conv1d_6[0][0]
__________________________________________________________________________________________________
activation_6 (Activation) (None, 2000, 64) 0 add_2[0][0]
__________________________________________________________________________________________________
max_pooling1d_2 (MaxPooling1D) (None, 1000, 64) 0 activation_6[0][0]
__________________________________________________________________________________________________
conv1d_11 (Conv1D) (None, 1000, 128) 24704 max_pooling1d_2[0][0]
__________________________________________________________________________________________________
activation_7 (Activation) (None, 1000, 128) 0 conv1d_11[0][0]
__________________________________________________________________________________________________
conv1d_12 (Conv1D) (None, 1000, 128) 49280 activation_7[0][0]
__________________________________________________________________________________________________
activation_8 (Activation) (None, 1000, 128) 0 conv1d_12[0][0]
__________________________________________________________________________________________________
conv1d_13 (Conv1D) (None, 1000, 128) 49280 activation_8[0][0]
__________________________________________________________________________________________________
conv1d_10 (Conv1D) (None, 1000, 128) 8320 max_pooling1d_2[0][0]
__________________________________________________________________________________________________
add_3 (Add) (None, 1000, 128) 0 conv1d_13[0][0]
conv1d_10[0][0]
__________________________________________________________________________________________________
activation_9 (Activation) (None, 1000, 128) 0 add_3[0][0]
__________________________________________________________________________________________________
max_pooling1d_3 (MaxPooling1D) (None, 500, 128) 0 activation_9[0][0]
__________________________________________________________________________________________________
conv1d_15 (Conv1D) (None, 500, 128) 49280 max_pooling1d_3[0][0]
__________________________________________________________________________________________________
activation_10 (Activation) (None, 500, 128) 0 conv1d_15[0][0]
__________________________________________________________________________________________________
conv1d_16 (Conv1D) (None, 500, 128) 49280 activation_10[0][0]
__________________________________________________________________________________________________