Hello,
I was testing with a custom tflite model where I noticed a significant drop in the model accuracy after tflite conversion. I understand this is expected but it was a float conversion, no optimization applied whatsoever. Not very sure what caused this.
Keras model accuracy: 85%
Float tflite model accuracy: 68%
The tflite conversion config is as follows.
converter = tf.lite.TFLiteConverter.from_keras_model(fixed_batch_model)
tfmodel = converter.convert()
Unfortunately can not upload the model due to company policies.
When I checked the model weights, even though they are in the same precision, they are different in the models. As per my understanding, this should not happen since we are not applying any optimization.
Clearly, I am missing some under-the-hood conversion step.
Please let me know what I am missing here.
Thanks a lot in advance.
Cheers,
Swaraj