From 3f3ab2bfe3ebfa266d433012be1c89c722d63352 Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Thu, 2 Jul 2015 11:15:37 -0400 Subject: Unify parameters for joint_simple_tgtcls_111_cswdtx_bigger{,_dropout} --- config/joint_simple_mlp_tgtcls_111_cswdtx_bigger.py | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) (limited to 'config/joint_simple_mlp_tgtcls_111_cswdtx_bigger.py') diff --git a/config/joint_simple_mlp_tgtcls_111_cswdtx_bigger.py b/config/joint_simple_mlp_tgtcls_111_cswdtx_bigger.py index 93ff5c7..8e991a1 100644 --- a/config/joint_simple_mlp_tgtcls_111_cswdtx_bigger.py +++ b/config/joint_simple_mlp_tgtcls_111_cswdtx_bigger.py @@ -29,14 +29,14 @@ dim_embeddings = [ # Common network part dim_input = n_begin_end_pts * 2 * 2 + sum(x for (_, _, x) in dim_embeddings) -dim_hidden = [1000] +dim_hidden = [5000] # Destination prediction part -dim_hidden_dest = [400] +dim_hidden_dest = [1000] dim_output_dest = dest_tgtcls.shape[0] # Time prediction part -dim_hidden_time = [400] +dim_hidden_time = [500] dim_output_time = len(time_tgtcls) # Cost ratio between distance cost and time cost @@ -46,8 +46,7 @@ embed_weights_init = IsotropicGaussian(0.01) mlp_weights_init = IsotropicGaussian(0.1) mlp_biases_init = Constant(0.01) -learning_rate = 0.000001 -momentum = 0.99 +# use adadelta, so no learning_rate or momentum batch_size = 200 valid_set = 'cuts/test_times_0' -- cgit v1.2.3