1

I am building a trainable USE model to do multiclass labeling. The input is a description string; the output should be 0, 1, or 2.

import tensorflow as tf
import tensorflow_hub as hub
import prep
module_url = "https://tfhub.dev/google/universal-sentence-encoder-large/5"
model = tf.keras.Sequential()
model.add(tf.keras.layers.Input(shape=[], name='sent1', dtype=tf.string))
model.add(hub.KerasLayer(module_url, trainable=True))
model.add(tf.keras.layers.Dense(3, activation='softmax', name='output'))

model.compile(loss='sparse_categorical_crossentropy',
              optimizer='adam', metrics=['accuracy'])
model.summary()
data = list(prep.read_jsonl('use/access_complexity/sample.jsonl'))
descriptions = [d['prompt'] for d in data]
labels = [int(d['completion']) for d in data]
model.fit(descriptions, labels, epochs=3)

gives the following error:

Model: "sequential"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 keras_layer (KerasLayer)    (None, 512)               147354880 
                                                                 
 output (Dense)              (None, 3)                 1539      
                                                                 
=================================================================
Total params: 147,356,419
Trainable params: 147,356,419
Non-trainable params: 0
_________________________________________________________________
Epoch 1/3
WARNING:tensorflow:Gradients do not exist for variables ['EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_0:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_1:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_2:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_3:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_4:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_5:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_6:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_7:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_8:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_9:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_10:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_11:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_12:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_13:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_14:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_15:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_16:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_17:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_18:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_19:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_20:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_21:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_22:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_23:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_24:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_25:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_26:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_27:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_28:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_29:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_0:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_1:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_2:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_3:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_4:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_5:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_6:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_7:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_8:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_9:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_10:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_11:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_12:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_13:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_14:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_15:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_16:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_17:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_18:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_19:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_20:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_21:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_22:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_23:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_24:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_25:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_26:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_27:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_28:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_29:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_0:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_1:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_2:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_3:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_4:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_5:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_6:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_7:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_8:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_9:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_10:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_11:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_12:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_13:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_14:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_15:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_16:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_17:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_18:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_19:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_20:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_21:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_22:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_23:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_24:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_25:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_26:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_27:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_28:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_29:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_0:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_1:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_2:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_3:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_4:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_5:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_6:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_7:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_8:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_9:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_10:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_11:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_12:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_13:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_14:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_15:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_16:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_17:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_18:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_19:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_20:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_21:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_22:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_23:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_24:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_25:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_26:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_27:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_28:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_29:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_0:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_1:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_2:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_3:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_4:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_5:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_6:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_7:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_8:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_9:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_10:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_11:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_12:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_13:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_14:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_15:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_16:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_17:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_18:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_19:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_20:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_21:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_22:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_23:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_24:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_25:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_26:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_27:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_28:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_29:0'] when minimizing the loss. If you're using `model.compile()`, did you forget to provide a `loss`argument?
WARNING:tensorflow:Gradients do not exist for variables ['EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_0:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_1:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_2:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_3:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_4:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_5:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_6:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_7:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_8:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_9:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_10:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_11:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_12:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_13:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_14:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_15:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_16:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_17:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_18:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_19:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_20:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_21:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_22:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_23:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_24:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_25:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_26:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_27:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_28:0', 'EncoderDNN/DNN/ResidualHidden_0/dense/kernel/part_29:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_0:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_1:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_2:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_3:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_4:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_5:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_6:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_7:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_8:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_9:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_10:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_11:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_12:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_13:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_14:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_15:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_16:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_17:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_18:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_19:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_20:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_21:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_22:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_23:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_24:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_25:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_26:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_27:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_28:0', 'EncoderDNN/DNN/ResidualHidden_1/dense/kernel/part_29:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_0:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_1:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_2:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_3:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_4:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_5:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_6:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_7:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_8:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_9:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_10:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_11:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_12:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_13:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_14:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_15:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_16:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_17:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_18:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_19:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_20:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_21:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_22:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_23:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_24:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_25:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_26:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_27:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_28:0', 'EncoderDNN/DNN/ResidualHidden_2/dense/kernel/part_29:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_0:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_1:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_2:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_3:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_4:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_5:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_6:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_7:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_8:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_9:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_10:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_11:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_12:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_13:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_14:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_15:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_16:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_17:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_18:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_19:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_20:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_21:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_22:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_23:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_24:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_25:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_26:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_27:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_28:0', 'EncoderDNN/DNN/ResidualHidden_3/dense/kernel/part_29:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_0:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_1:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_2:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_3:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_4:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_5:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_6:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_7:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_8:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_9:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_10:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_11:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_12:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_13:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_14:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_15:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_16:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_17:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_18:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_19:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_20:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_21:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_22:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_23:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_24:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_25:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_26:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_27:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_28:0', 'EncoderDNN/DNN/ResidualHidden_3/AdjustDepth/projection/kernel/part_29:0'] when minimizing the loss. If you're using `model.compile()`, did you forget to provide a `loss`argument?
1/1 [==============================] - ETA: 0s - loss: 1.0627 - accuracy: 1/1 [==============================] - 58s 58s/step - loss: 1.0627 - accuracy: 0.6667
Epoch 2/3
1/1 [==============================] - ETA: 0s - loss: 0.7200 - accuracy: 1/1 [==============================] - 2s 2s/step - loss: 0.7200 - accuracy: 1.0000
Epoch 3/3
1/1 [==============================] - ETA: 0s - loss: 0.4957 - accuracy: 1/1 [==============================] - 2s 2s/step - loss: 0.4957 - accuracy: 1.0000
Zingg
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    The message is a warning, not an error, please do not confuse the two. – Dr. Snoopy Mar 17 '22 at 02:34
  • The warning is due to the unconnected gradient. For an explanation please refer to this similar [issue](https://stackoverflow.com/questions/57144586/tensorflow-gradienttape-gradients-does-not-exist-for-variables-intermittently). Thank You. –  Sep 14 '22 at 04:26
  • I don’t think it’s unconnected gradient. The model has only one extra layer, assuming USE was made without such errors from Google’s side. – Zingg Sep 15 '22 at 05:10
  • Hi Have you solved the problem? I met a similar one.. – stander Qiu Dec 28 '22 at 07:08
  • @standerQiu Yes, I got the USE model to work by tweaking the learning rate. – Zingg Jan 25 '23 at 04:01
  • @Zingg what means "USE" model ? Do you mean that you've just set right optimizer learning_rate ? – JulJ Mar 23 '23 at 20:18
  • @luliia Universal Sentence Encoder(USE). – Zingg Mar 24 '23 at 21:05

1 Answers1

1

Solved by lowering learning rate.

Zingg
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