# Using Trainable=True in Keras Embedding obtained better performance

It is suggested by the author of Keras [1] to use Trainable=False when using the embedding layer in Keras to prevent the weights from being updated during training. But in my experience, I always got better performance (lower error in regression) when setting Trainable=True in text processing.

My question, can I claim my result or I must use Trainable=False? Do I make a cheat when using Trainable=True?

According to my understanding, it just a choice to use (or not to use) previous information to update the weight, so it is allowed to use Trainable=True.

If for your set of tasks were you use Embedding layer you consistently get lower test error, and the requirement does not specifically say so to use trainable=False for Embedding layer - why bother? It is not cheating.