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-rw-r--r--dtrain/dtrain.cc4
1 files changed, 2 insertions, 2 deletions
diff --git a/dtrain/dtrain.cc b/dtrain/dtrain.cc
index b7a4bb6f..18286668 100644
--- a/dtrain/dtrain.cc
+++ b/dtrain/dtrain.cc
@@ -24,13 +24,13 @@ dtrain_init(int argc, char** argv, po::variables_map* cfg)
("pair_threshold", po::value<score_t>()->default_value(0.), "bleu [0,1] threshold to filter pairs")
("N", po::value<unsigned>()->default_value(4), "N for Ngrams (BLEU)")
("scorer", po::value<string>()->default_value("stupid_bleu"), "scoring: bleu, stupid_, smooth_, approx_, lc_")
- ("learning_rate", po::value<weight_t>()->default_value(0.0001), "learning rate")
+ ("learning_rate", po::value<weight_t>()->default_value(1.0), "learning rate")
("gamma", po::value<weight_t>()->default_value(0.), "gamma for SVM (0 for perceptron)")
("select_weights", po::value<string>()->default_value("last"), "output best, last, avg weights ('VOID' to throw away)")
("rescale", po::value<bool>()->zero_tokens(), "rescale weight vector after each input")
("l1_reg", po::value<string>()->default_value("none"), "apply l1 regularization as in 'Tsuroka et al' (2010)")
("l1_reg_strength", po::value<weight_t>(), "l1 regularization strength")
- ("fselect", po::value<weight_t>()->default_value(-1), "select top x percent (or by threshold) of features after each epoch NOT IMPL") // TODO
+ ("fselect", po::value<weight_t>()->default_value(-1), "select top x percent (or by threshold) of features after each epoch NOT IMPLEMENTED") // TODO
("approx_bleu_d", po::value<score_t>()->default_value(0.9), "discount for approx. BLEU")
("scale_bleu_diff", po::value<bool>()->zero_tokens(), "learning rate <- bleu diff of a misranked pair")
("loss_margin", po::value<weight_t>()->default_value(0.), "update if no error in pref pair but model scores this near")