def Task(cls): p = base_config.SetupTransformerParams( name='wmt14_en_de_transformer_base', vocab_size=cls.VOCAB_SIZE, model_dim=512, hidden_dim=2048, num_heads=8, num_layers=6, residual_dropout_prob=0.1, input_dropout_prob=0.1, learning_rate=3.0, warmup_steps=40000) p.eval.samples_per_summary = 7500 return p
def Task(cls): p = base_config.SetupTransformerParams( name='wmt14_en_de_transformer_base', vocab_size=cls.VOCAB_SIZE, model_dim=256, hidden_dim=512, num_heads=2, num_layers=2, residual_dropout_prob=0.2, input_dropout_prob=0.2, learning_rate=1.0, warmup_steps=1000) p.eval.samples_per_summary = 7500 p.train.save_interval_seconds = 60 p.train.max_steps = 12000 return p