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I am working with character level cnn model for sentence classification, and I used keras framework to build my model. However, model compilation was good, but when I tried to fit my model I faced following embedding lookup error:

Train on 10240 samples, validate on 1284 samples

Epoch 1/30

---------------------------------------------------------------------------

InvalidArgumentError                      Traceback (most recent call last)

<ipython-input-57-15a1aa414e1a> in <module>

      1 history_char= model_char.fit(x_train,y_train,epochs=num_epochs, batch_size=batch_size,

----> 2                                validation_data=(x_val,y_val))

      3 

      4 # model_char.fit(x_train,y_train,epochs=10, batch_size=64, validation_data=(x_val, y_val))



~AppDataLocalContinuumanaconda3libsite-packageskerasenginetraining.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, **kwargs)

   1037                                         initial_epoch=initial_epoch,

   1038                                         steps_per_epoch=steps_per_epoch,

-> 1039                                         validation_steps=validation_steps)

   1040 

   1041     def evaluate(self, x=None, y=None,



~AppDataLocalContinuumanaconda3libsite-packageskerasenginetraining_arrays.py in fit_loop(model, f, ins, out_labels, batch_size, epochs, verbose, callbacks, val_f, val_ins, shuffle, callback_metrics, initial_epoch, steps_per_epoch, validation_steps)

    197                     ins_batch[i] = ins_batch[i].toarray()

    198 

--> 199                 outs = f(ins_batch)

    200                 outs = to_list(outs)

    201                 for l, o in zip(out_labels, outs):



~AppDataLocalContinuumanaconda3libsite-packageskerasbackendtensorflow_backend.py in __call__(self, inputs)

   2713                 return self._legacy_call(inputs)

   2714 

-> 2715             return self._call(inputs)

   2716         else:

   2717             if py_any(is_tensor(x) for x in inputs):



~AppDataLocalContinuumanaconda3libsite-packageskerasbackendtensorflow_backend.py in _call(self, inputs)

   2673             fetched = self._callable_fn(*array_vals, run_metadata=self.run_metadata)

   2674         else:

-> 2675             fetched = self._callable_fn(*array_vals)

   2676         return fetched[:len(self.outputs)]

   2677 



~AppDataLocalContinuumanaconda3libsite-packagestensorflowpythonclientsession.py in __call__(self, *args, **kwargs)

   1437           ret = tf_session.TF_SessionRunCallable(

   1438               self._session._session, self._handle, args, status,

-> 1439               run_metadata_ptr)

   1440         if run_metadata:

   1441           proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)



~AppDataLocalContinuumanaconda3libsite-packagestensorflowpythonframeworkerrors_impl.py in __exit__(self, type_arg, value_arg, traceback_arg)

    526             None, None,

    527             compat.as_text(c_api.TF_Message(self.status.status)),

--> 528             c_api.TF_GetCode(self.status.status))

    529     # Delete the underlying status object from memory otherwise it stays alive

    530     # as there is a reference to status from this from the traceback due to



InvalidArgumentError: indices[120,0] = 516 is not in [0, 70)

     [[{{node embedding_14/embedding_lookup}}]]

here is basic architecture of keras model (screenshot):