def Task(cls):
return base_config.SetupRNMTParams(
model.RNMTModel.Params(),
name='punctuator_rnmt',
vocab_size=cls._VOCAB_SIZE,
embedding_dim=1024,
hidden_dim=1024,
num_heads=4,
num_encoder_layers=6,
num_decoder_layers=8,
learning_rate=1e-4,
l2_regularizer_weight=1e-5,
lr_warmup_steps=500,
lr_decay_start=400000,
lr_decay_end=1200000,
lr_min=0.5,
ls_uncertainty=0.1,
atten_dropout_prob=0.3,
residual_dropout_prob=0.3,
adam_beta2=0.98,
adam_epsilon=1e-6,
)
def Task(cls):
p = base_config.SetupRNMTParams(
name='wmt14_en_de_rnmtplus_base',
vocab_size=cls.VOCAB_SIZE,
embedding_dim=1024,
hidden_dim=1024,
num_heads=4,
num_encoder_layers=6,
num_decoder_layers=8,
learning_rate=1e-4,
l2_regularizer_weight=1e-5,
lr_warmup_steps=500,
lr_decay_start=400000,
lr_decay_end=1200000,
lr_min=0.5,
ls_uncertainty=0.1,
atten_dropout_prob=0.3,
residual_dropout_prob=0.3,
adam_beta2=0.98,
adam_epsilon=1e-6,
)
p.eval.samples_per_summary = 7500
return p
