这个问题是因为标签y_train包含的整数大于指定的间隔[0, 128)，因为Embedding层的输出大小设置为128。
让我们用一个简化的例子来说明这一点。在这里，我将形状从(100082, 1307)减少到(1000, 1307)：
我们使用随机生成器创建y_trainTensor，如下所示：

y_train = tf.random.uniform(shape=([1000, 1307]), minval=0, maxval=127)

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这里我们测试10个epoch：

model = Sequential([
    Embedding(total_tokens, 128, input_length=max_seq_length),
])
model.summary()
model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=1e-4),
              loss='sparse_categorical_crossentropy',
              metrics=['accuracy'])
model.fit(X_train, y_train, epochs=10)

型
下面是输出：

Model: "sequential_1"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 embedding_1 (Embedding)     (None, 1307, 128)         128000    
                                                                 
=================================================================
Total params: 128000 (500.00 KB)
Trainable params: 128000 (500.00 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 1/10
32/32 [==============================] - 4s 124ms/step - loss: 10.5185 - accuracy: 0.0000e+00
Epoch 2/10
32/32 [==============================] - 5s 152ms/step - loss: 10.4612 - accuracy: 0.0000e+00
Epoch 3/10
32/32 [==============================] - 4s 116ms/step - loss: 10.4123 - accuracy: 0.0000e+00
Epoch 4/10
32/32 [==============================] - 4s 116ms/step - loss: 10.3636 - accuracy: 0.0000e+00
Epoch 5/10
32/32 [==============================] - 6s 175ms/step - loss: 10.3126 - accuracy: 0.0000e+00
Epoch 6/10
32/32 [==============================] - 4s 120ms/step - loss: 10.2577 - accuracy: 0.0000e+00
Epoch 7/10
32/32 [==============================] - 4s 119ms/step - loss: 10.1967 - accuracy: 0.0000e+00
Epoch 8/10
32/32 [==============================] - 5s 152ms/step - loss: 10.1267 - accuracy: 0.0000e+00
Epoch 9/10
32/32 [==============================] - 4s 119ms/step - loss: 10.0431 - accuracy: 0.0000e+00
Epoch 10/10
32/32 [==============================] - 4s 119ms/step - loss: 9.9369 - accuracy: 7.6511e-07
<keras.src.callbacks.History at 0x7de0b88f0ee0>

型
在此示例中，模型运行时没有错误。
但是，如果生成器的上限设置为200（大于128）：

y_train = tf.random.uniform(shape=([1000, 1307]), minval=0, maxval=200)

型
出现错误：

Received a label value of 199 which is outside the valid range of [0, 128).

型
因此，您应该确保y_train中的标签在Embedding图层的输出大小指定的有效范围内。