history = lipnet.model.fit(x = [X_train, y_train, input_length_X, label_length_X], y = y_train, validation_data = [X_val, y_val, input_length_v, label_length_v], batch_size = 8, epochs=100, verbose= 1, callbacks=[checkpoint, early_stopping], initial_epoch=0)

ValueError Traceback (most recent call last)
Cell In[18], line 1
—-> 1 history = lipnet.model.fit(x = [X_train, y_train, input_length_X, label_length_X], y = y_train, validation_data = [X_val, y_val, input_length_v, label_length_v], batch_size = 8, epochs=100, verbose= 1, callbacks=[checkpoint, early_stopping], initial_epoch=0)

File ~anaconda3Libsite-packageskerassrcutilstraceback_utils.py:122, in filter_traceback..error_handler(*args, **kwargs)
119 filtered_tb = _process_traceback_frames(e.traceback)
120 # To get the full stack trace, call:
121 # keras.config.disable_traceback_filtering()
–> 122 raise e.with_traceback(filtered_tb) from None
123 finally:
124 del filtered_tb

File ~anaconda3Libsite-packageskerassrctrainersdata_adaptersdata_adapter_utils.py:50, in unpack_x_y_sample_weight(data)
45 return (data[0], data[1], data[2])
46 error_msg = (
47 “Data is expected to be in format x, (x,), (x, y), ”
48 f”or (x, y, sample_weight), found: {data}”
49 )
—> 50 raise ValueError(error_msg)

ValueError: Data is expected to be in format x, (x,), (x, y), or (x, y, sample_weight), found: (array([[0., 0., 0., …, 0., 0., 0.],
[0., 0., 0., …, 0., 0., 0.],
[0., 0., 0., …, 0., 0., 0.],
…,(Omitted below)