ValueError: `logits` and `labels` must have the same shape, received ((None, 10)...

Question

Kerasで次の単語を予測するプログラムを書こうとしています。
参考にしている動画はこちら
（https://www.youtube.com/watch?v=VB7bbFIEAhk)
で、以下のように実行しました(14:00あたりです）

from tensorflow.keras.callbacks import ModelCheckpoint

checkpoint = ModelCheckpoint("next_words.h5", monitor = 'loss', verbose = 1, save_best_only = True)
model.compile(loss = "BinaryCrossentropy", optimizer=Adam(learning_rate = 0.001))
model.fit(X, y, epochs = 70, batch_size = 64, callbacks = [checkpoint])

すると、以下のようなエラーが出ます。

Epoch 1/70
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-56-27002549d528> in <module>()
      3 checkpoint = ModelCheckpoint("next_words.h5", monitor = 'loss', verbose = 1, save_best_only = True)
      4 model.compile(loss = "BinaryCrossentropy", optimizer=Adam(learning_rate = 0.001))
----> 5 model.fit(X, y, epochs = 70, batch_size = 64, callbacks = [checkpoint])

1 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/func_graph.py in autograph_handler(*args, **kwargs)
   1145           except Exception as e:  # pylint:disable=broad-except
   1146             if hasattr(e, "ag_error_metadata"):
-> 1147               raise e.ag_error_metadata.to_exception(e)
   1148             else:
   1149               raise

ValueError: in user code:

    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1021, in train_function  *
        return step_function(self, iterator)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1010, in step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 1000, in run_step  **
        outputs = model.train_step(data)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 860, in train_step
        loss = self.compute_loss(x, y, y_pred, sample_weight)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/training.py", line 919, in compute_loss
        y, y_pred, sample_weight, regularization_losses=self.losses)
    File "/usr/local/lib/python3.7/dist-packages/keras/engine/compile_utils.py", line 201, in __call__
        loss_value = loss_obj(y_t, y_p, sample_weight=sw)
    File "/usr/local/lib/python3.7/dist-packages/keras/losses.py", line 141, in __call__
        losses = call_fn(y_true, y_pred)
    File "/usr/local/lib/python3.7/dist-packages/keras/losses.py", line 245, in call  **
        return ag_fn(y_true, y_pred, **self._fn_kwargs)
    File "/usr/local/lib/python3.7/dist-packages/keras/losses.py", line 1932, in binary_crossentropy
        backend.binary_crossentropy(y_true, y_pred, from_logits=from_logits),
    File "/usr/local/lib/python3.7/dist-packages/keras/backend.py", line 5247, in binary_crossentropy
        return tf.nn.sigmoid_cross_entropy_with_logits(labels=target, logits=output)

    ValueError: `logits` and `labels` must have the same shape, received ((None, 10) vs (None, 10, 10)).

文献もなく、途方に暮れています。どなたかお詳しい方、ご教授いただけると幸いです。

Answer 1

lossを

model.compile(loss = "categorical_crossentropy", optimizer=Adam(learning_rate = 0.001))

としたら別のエラーが出たのでひとまずこの問題は解決したっぽいです。