Model accuracy reduction in .tflite modelw

I’m currently developing some model optimization using TensorFlow by trying different features (quantization, weight pruning…) in some of my company models.
My problem comes when I convert an h5 model to .tflite without any type of special optimization with the following code:

converter = tf.lite.TFLiteConverter.from_keras_model(model)
tflite_model = converter.convert()
with open('model.tflite', 'wb') as f:

The model (MobileNet v2) size went from 18.5 MB to 8.9 MB and accuracy from 99.48% to 98.51%
I can’t explain this change that is also happening in other models, for example, this ResNet50:
94.9MB to 94MB and 98.51% to 94.51%.

Why is the conversion to .tflite reducing weight and accuracy without any type of extra optimization?