Val_loss, loss and accuracy all zero

Question

need some explanation here. This ANN with physics equation has been run by my team member on another laptop and it showed converged val_loss, loss and accuracy. However, all the losses become zero when I run at my site. Anyone know why ?

from tensorflow import keras
from tensorflow.keras.layers import Input, Dense, Dropout, Lambda, Add
from tensorflow.keras.models import Model
from tensorflow.keras import Variable
import tensorflow.keras.backend as K
from tensorflow.keras.losses import MAPE
from tensorflow.keras.losses import MeanSquaredLogarithmicError as MSLE
#Ann Input Features
ann_input_features = Input(shape=(11,),name='Ann_input_features_1')

#Input for T1 and Compressor Efficiency
T1_input = Input(shape=(1,), name='T1_Input')
pi_c_input = Input(shape=(1,), name='pi_c_Input')

#ANN Sequetial
Layer_1 = Dense(96,activation='tanh',name='Layer_2')(ann_input_features)
#Physics Output
physics_out= Lambda(lambda x: compressor_discharge_temp(x[0], x[1]),output_shape=(1,),name='Physics_Out')([T1_input,pi_c_input])

#ANN OUTPUT
ann_out = Dense(1,name='Ann_Output')(Layer_1)
ann_output_model_1= Model(inputs=ann_input_features,outputs=ann_out)
learning_rate = 0.001
optimizer = Adam(learning_rate=learning_rate)
ann_output_model_1.compile(optimizer=optimizer,loss='MSLE')

ann_output = ann_output_model_1(ann_input_features)

#ann_out_2= ann_model(ann_input_features)
w = K.variable(0.50,name='Weight')

#ann_out = Dense(1)(ann_layer_1)
pinn_out = Lambda(lambda x:(w*x[0]+(1-w)*x[1]),dtype=tf.float64,output_shape=(1,),name='PINN_out')([ann_output,physics_out])

# Use specified learning rate with optimizer
learning_rate = 0.001
optimizer = Adam(learning_rate=learning_rate,epsilon = 1e-10,clipnorm=0.001) # The optimizer to be used

ann_output_model = Model(inputs=[ann_input_features,T1_input,pi_c_input],outputs=pinn_out)
ann_output_model.compile(optimizer=optimizer,loss='MSLE',metrics=['accuracy'])
ann_output_model.summary()

ann_output_model.fit([X_val,Val_T1,Val_pi_c],Val_target_sept,epochs=50,batch_size=32,validation_data=([X_train,Train_T1,Train_pi_c], Train_target_oct))

I have tried to change the learning rate to low and high. I also tried to change the optimizer but the result didn't change.