Can get the model evaluation to succeed thinking there is something wrong with the trained model.
Followed the turorial on:
  
      

      TensorFlow
  

  
    

Object Detection with TensorFlow Lite Model Maker 3



  

  
    
    
  

  


Ran:
train_data, validation_data, test_data = object_detector.DataLoader.from_csv('my-dataset.csv')

model_arch = 'efficientdet_lite0'
spec = model_spec.get(model_arch)

EPOCHS = 20
model = object_detector.create(train_data, model_spec=spec, epochs=EPOCHS, batch_size=64, train_whole_model=True, validation_data=validation_data)

.
.
.
Epoch 20/20
513/513 [========================] - 108s 211ms/step - det_loss: 0.0851 - cls_loss: 0.0691 - box_loss: 3.1992e-04 - reg_l2_loss: 0.0627 - loss: 0.1477 - learning_rate: 2.2774e-05 - gradient_norm: 1.1593 - val_det_loss: 0.0648 - val_cls_loss: 0.0523 - val_box_loss: 2.5131e-04 - val_reg_l2_loss: 0.0627 - val_loss: 0.1275

And then:
loss, accuracy = model.evaluate(test_data)

*ValueError: too many values to unpack (expected 2)*

Dataset splits (image size 500x300):

Training Set - 4.8k images  92%
Validation Set 271 images   5%
Testing Set 135  images       3%