07 Milestone 1 Food Vision Fine-Tuning Model Error

[supermarios77]

Whilst fine-tuning my model i get this error

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
[<ipython-input-44-2537ab604f4a>](https://localhost:8080/#) in <cell line: 7>()
      5 early_stopping = tf.keras.callbacks.EarlyStopping(monitor="val_loss", patience=3)
      6 
----> 7 history_fine_tuned = model.fit(train_data,
      8                                epochs=fine_tune_epochs,
      9                                steps_per_epoch=len(train_data),

1 frames
[/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py](https://localhost:8080/#) in tf__train_function(iterator)
     13                 try:
     14                     do_return = True
---> 15                     retval_ = ag__.converted_call(ag__.ld(step_function), (ag__.ld(self), ag__.ld(iterator)), None, fscope)
     16                 except:
     17                     do_return = False

ValueError: in user code: 

 File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1338, in train_function  *
        return step_function(self, iterator)
    File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1322, in step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1303, in run_step  **
        outputs = model.train_step(data)
    File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1081, in train_step
        loss = self.compute_loss(x, y, y_pred, sample_weight)
    File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1139, in compute_loss
        return self.compiled_loss(
    File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/compile_utils.py", line 265, in __call__
        loss_value = loss_obj(y_t, y_p, sample_weight=sw)
    File "/usr/local/lib/python3.10/dist-packages/keras/src/losses.py", line 142, in __call__
        losses = call_fn(y_true, y_pred)
    File "/usr/local/lib/python3.10/dist-packages/keras/src/losses.py", line 268, in call  **
        return ag_fn(y_true, y_pred, **self._fn_kwargs)
    File "/usr/local/lib/python3.10/dist-packages/keras/src/losses.py", line 2122, in categorical_crossentropy
        return backend.categorical_crossentropy(
    File "/usr/local/lib/python3.10/dist-packages/keras/src/backend.py", line 5560, in categorical_crossentropy
        target.shape.assert_is_compatible_with(output.shape)

    ValueError: Shapes (None, 1) and (None, 101) are incompatible

    File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1338, in train_function  *
        return step_function(self, iterator)
    File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1322, in step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1303, in run_step  **
        outputs = model.train_step(data)
    File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1081, in train_step
        loss = self.compute_loss(x, y, y_pred, sample_weight)
    File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1139, in compute_loss
        return self.compiled_loss(
    File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/compile_utils.py", line 265, in __call__
        loss_value = loss_obj(y_t, y_p, sample_weight=sw)
    File "/usr/local/lib/python3.10/dist-packages/keras/src/losses.py", line 142, in __call__
        losses = call_fn(y_true, y_pred)
    File "/usr/local/lib/python3.10/dist-packages/keras/src/losses.py", line 268, in call  **
        return ag_fn(y_true, y_pred, **self._fn_kwargs)
    File "/usr/local/lib/python3.10/dist-packages/keras/src/losses.py", line 2122, in categorical_crossentropy
        return backend.categorical_crossentropy(
    File "/usr/local/lib/python3.10/dist-packages/keras/src/backend.py", line 5560, in categorical_crossentropy
        target.shape.assert_is_compatible_with(output.shape)

    ValueError: Shapes (None, 1) and (None, 101) are incompatible

Here is my code:

# Fine-tune the model and use early_stopping callback

fine_tune_epochs = 100

early_stopping = tf.keras.callbacks.EarlyStopping(monitor="val_loss", patience=3)

history_fine_tuned = model.fit(train_data,
                               epochs=fine_tune_epochs, 
                               steps_per_epoch=len(train_data),
                               validation_data=test_data,
                               validation_steps=int(0.15 * len(test_data)),
                               initial_epoch=history_101_food_classes_feature_extract.epoch[-1],
                               callbacks=[create_tensorboard_callback("training_logs", "fine-tuned-model"), 
                                          model_checkpoint,
                                          early_stopping])

[mrdbourke]

Hi @supermarios77 ,

It looks like your model shapes may be different to your data shapes.

The error:

ValueError: Shapes (None, 1) and (None, 101) are incompatible

Is suggesting that maybe your model was trained on a shape of (None, 1) where as you data is (None, 101) -- can you check the shapes of your model's output layer/shape of your data?

[supermarios77]

Ok, thanks, The shapes were wrong it's fixed now.