InvalidArgumentError (see above for traceback): **indices[6,4]** = 23624 is not in [0, 23624)

I get the following error after running an embedding layer as;

Embedding(23624, 50, input_length=5, trainable=False)

InvalidArgumentError (see above for traceback): indices[6,4] = 23624 is not in [0, 23624)
[[Node: embedding_1/embedding_lookup = Gather[Tindices=DT_INT32, Tparams=DT_FLOAT, _class=["loc:@embedding_1/embeddings"], validate_indices=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](embedding_1/embeddings/read, embedding_1/Cast)]]

Each datapoint here is a number(index). Upon checking indices[6,4] I found the following

print(ar_train_data[6,4])
5088

ar_train_data is an array of shape (162896, 5) where each value is between [0, 23624).
The training stops towards the end of the first epoch with the error above.

Am amazed! 5088 is no where out of range for [0, 23624). Can anyone suggest what could be the issue here?
Please suggest if additional code snippets are required for clarity.
The model roughly goes below as:

inputs =  Input(shape=(None,),dtype='float32')
               <Embedding layer>
               <Convolution layer>
linear_output = Dense(10,input_shape=(72,),activation='relu')(linear_input)

model = Model(inputs=[inputs],outputs=[linear_output])
model.compile(loss='categorical_crossentropy', optimizer='nadam')

Keras version - 2.2.4
tensorflow version: 1.5.0

Regards

Start with the model entry point shown in the issue, especially the Embedding layer input and the training data represented by ar_train_data. Reproduce the first-epoch failure and compare the value reaching the layer with the printed source value; done means identifying and documenting why an out-of-range index reaches the embedding.