diff options
Diffstat (limited to 'config/dest_simple_mlp_emb_only.py')
| -rw-r--r-- | config/dest_simple_mlp_emb_only.py | 22 |
1 files changed, 11 insertions, 11 deletions
diff --git a/config/dest_simple_mlp_emb_only.py b/config/dest_simple_mlp_emb_only.py index e5c91b8..76acdfa 100644 --- a/config/dest_simple_mlp_emb_only.py +++ b/config/dest_simple_mlp_emb_only.py @@ -6,26 +6,26 @@ from model.mlp_emb import Model, Stream use_cuts_for_training = True dim_embeddings = [ - ('origin_call', data.origin_call_train_size, 10), - ('origin_stand', data.stands_size, 10), - ('week_of_year', 52, 10), - ('day_of_week', 7, 10), + # ('origin_call', data.origin_call_train_size, 100), + # ('origin_stand', data.stands_size, 100), + # ('week_of_year', 52, 100), + # ('day_of_week', 7, 100), ('qhour_of_day', 24 * 4, 10), - ('day_type', 3, 10), + ('day_type', 3, 1), ] dim_input = sum(x for (_, _, x) in dim_embeddings) -dim_hidden = [200, 100] +dim_hidden = [10, 10] output_mode = "destination" dim_output = 2 -embed_weights_init = IsotropicGaussian(0.001) +embed_weights_init = IsotropicGaussian(0.01) mlp_weights_init = IsotropicGaussian(0.01) -mlp_biases_init = Constant(0.001) +mlp_biases_init = IsotropicGaussian(0.001) -learning_rate = 0.0001 -momentum = 0.99 -batch_size = 32 +learning_rate = 0.001 +momentum = 0.9 +batch_size = 100 valid_set = 'cuts/test_times_0' max_splits = 100 |