From 7dfd1aca7117c0a15cf2377741d0a18b212cf2cb Mon Sep 17 00:00:00 2001
From: cloudygoose <cloudygooseg@gmail.com>
Date: Sun, 15 Nov 2015 17:30:41 +0800
Subject: got good PPL for H400...

---
 nerv/examples/lmptb/tnn_ptb_main.lua | 21 +++++++++++----------
 1 file changed, 11 insertions(+), 10 deletions(-)

diff --git a/nerv/examples/lmptb/tnn_ptb_main.lua b/nerv/examples/lmptb/tnn_ptb_main.lua
index 00fc12d..e9631ba 100644
--- a/nerv/examples/lmptb/tnn_ptb_main.lua
+++ b/nerv/examples/lmptb/tnn_ptb_main.lua
@@ -157,21 +157,22 @@ local set = arg[1] --"test"
 if (set == "ptb") then
 
 data_dir = '/home/slhome/txh18/workspace/nerv/nerv/nerv/examples/lmptb/PTBdata'
-train_fn = data_dir .. '/ptb.valid.txt.adds'
+train_fn = data_dir .. '/ptb.train.txt.adds'
 valid_fn = data_dir .. '/ptb.valid.txt.adds'
 test_fn = data_dir .. '/ptb.test.txt.adds'
 vocab_fn = data_dir .. '/vocab'
 
 global_conf = {
-    lrate = 1, wcost = 1e-6, momentum = 0,
+    lrate = 1, wcost = 1e-5, momentum = 0,
     cumat_type = nerv.CuMatrixFloat,
     mmat_type = nerv.MMatrixFloat,
     nn_act_default = 0, 
 
-    hidden_size = 300,
+    hidden_size = 400,
     chunk_size = 15,
     batch_size = 10, 
-    max_iter = 30,
+    max_iter = 35,
+    decay_iter = 16,
     param_random = function() return (math.random() / 5 - 0.1) end,
 
     train_fn = train_fn,
@@ -191,7 +192,7 @@ test_fn = '/home/slhome/txh18/workspace/nerv/nerv/nerv/examples/lmptb/m-tests/so
 vocab_fn = '/home/slhome/txh18/workspace/nerv/nerv/nerv/examples/lmptb/m-tests/some-text'
 
 global_conf = {
-    lrate = 1, wcost = 1e-6, momentum = 0,
+    lrate = 1, wcost = 1e-5, momentum = 0,
     cumat_type = nerv.CuMatrixFloat,
     mmat_type = nerv.CuMatrixFloat,
     nn_act_default = 0, 
@@ -297,7 +298,7 @@ for iter = start_iter, global_conf.max_iter, 1 do
     result = LMTrainer.lm_process_file(global_conf, global_conf.valid_fn, tnn, false) --false update!
     ppl_rec[iter].valid = result:ppl_all("rnn") 
     ppl_rec[iter].lr = global_conf.lrate 
-    if (ppl_last / ppl_rec[iter].valid < 1.0003 or lr_half == true) then 
+    if ((ppl_last / ppl_rec[iter].valid < 1.0003 or lr_half == true) and iter > global_conf.decay_iter) then 
         global_conf.lrate = (global_conf.lrate * 0.6)
     end 
     if (ppl_rec[iter].valid < ppl_last) then 
@@ -306,10 +307,10 @@ for iter = start_iter, global_conf.max_iter, 1 do
     else 
         printf("%s PPL did not improve, rejected, copying param file of last iter...\n", global_conf.sche_log_pre) 
         os.execute('cp ' .. global_conf.param_fn..'.'..tostring(iter - 1) .. ' ' .. global_conf.param_fn..'.'..tostring(iter))
-        if (lr_half == true) then
-            printf("%s LR is already halfing, end training...\n", global_conf.sche_log_pre)
-            break
-        end
+        --if (lr_half == true) then
+        --    printf("%s LR is already halfing, end training...\n", global_conf.sche_log_pre)
+        --    break
+        --end
     end 
     if (ppl_last / ppl_rec[iter].valid < 1.0003 or lr_half == true) then 
         lr_half = true
-- 
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