Comments (1)
Hi,
indeed, the hyperparameters that are in the config.py
file aren't probably the optimal for any task. The choice of hyperparameters greatly depends on the task. I can recommend the following changes (but probably other setups are valid too):
-
Change your learning rate. You'll probably need to tune it (try e.g.
LR = 0.0002
). -
Increment the size of your network:
SOURCE_TEXT_EMBEDDING_SIZE
,TARGET_TEXT_EMBEDDING_SIZE
,ENCODER_HIDDEN_SIZE
andDECODER_HIDDEN_SIZE
(try values of 256 or higher). -
Try to inject some noise to the weights during training (
USE_NOISE = True
) -
Try to apply dropout:
DROPOUT_P = 0.1
andATTENTION_DROPOUT_P = 0.1
and a small smoothing on labelsLABEL_SMOOTHING = 0.05
-
The application of byte-pair-encoding is also recommended.
For knowing more about the scores reported during training, please follow the references appearing in coco-caption. There you'll got links to those metrics.
from nmt-keras.
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from nmt-keras.