licence

LICENCE

@@ -0,0 +1,21 @@
+The MIT License (MIT)
+
+Copyright (c) <2015> <Yoon Kim>
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+THE SOFTWARE.

README.md

@@ -38,30 +38,34 @@ widely used by the language modeling community) is given as the default.
 ### Model
 Here are some example scripts.
 
-LSTM-CharCNN-Large (this is the default: should get ~82 on dev and ~79 on test)
+Large character-level model (`LSTM-CharCNN-Large' in the paper).
+This is the default: should get ~82 on valid and ~79 on test.
 ```
 th main.lua -gpuid 0 -savefile char-large
 ```
 
-LSTM-CharCNN-Small (should get ~96 on dev and ~93 on test)
+Small character-level model ('LSTM-CharCNN-Small' in the paper).
+This should get ~96 on valid and ~93 on test.
 ```
 th main.lua -gpuid 0 -savefile char-small -rnn_size 300 -highway_layers 1 
 -kernels '{1,2,3,4,5,6}' -feature_maps '{25,50,75,100,125,150}'
 ```
 
-LSTM-Word-Large (should get ~89 on dev and ~85 on test)
+Large word-level model.
+This should get ~89 on valid and ~85 on test.
 ```
 th main.lua -gpuid 0 -savefile word-large -word_vec_size 650 -highway_layers 0 
 -use_chars 0 -use_words 1
 ```
 
-LSTM-Word-Small (should get ~101 on dev and ~98 on test)
+Small word-level model.
+This should get ~101 on valid and ~98 on test.
 ```
 th main.lua -gpuid 0 -savefile word-small -word_vec_size 200 -highway_layers 0 
 -use_chars 0 -use_words 1 -rnn_size 200
 ```
 
-Note that if `-use_chars` and `-use_words` is both set to 1, the model
+Note that if `-use_chars` and `-use_words` are both set to 1, the model
 will concatenate the output from the CNN with the word embedding. We've
 found this model to underperform a purely character-level model, though.