CS224n
CS224n: Natural Language Processing with Deep Learning Assignments Winter, 2017
Requirements
- Python 2.7
- TensorFlow r1.2
Assignment #1
- Softmax
- Neural Network Basics
- word2vec
- Sentiment Analysis
Assignment #2
- Tensorflow Softmax
- Neural Transition-Based Dependency Parsing
924/924 [==============================] - 49s - train loss: 0.0631
Evaluating on dev set - dev UAS: 88.54
New best dev UAS! Saving model in ./data/weights/parser.weights
================================================================================
TESTING
================================================================================
Restoring the best model weights found on the dev set
Final evaluation on test set - test UAS: 88.92
Writing predictions
Done!
- Recurrent Neural Networks: Language Modeling
Assignment #3
- A window into NER
DEBUG:Token-level confusion matrix:
go\gu PER ORG LOC MISC O
PER 2968 26 84 16 55
ORG 147 1621 131 65 128
LOC 48 88 1896 26 36
MISC 37 40 54 1030 107
O 42 46 18 39 42614
DEBUG:Token-level scores:
label acc prec rec f1
PER 0.99 0.92 0.94 0.93
ORG 0.99 0.89 0.77 0.83
LOC 0.99 0.87 0.91 0.89
MISC 0.99 0.88 0.81 0.84
O 0.99 0.99 1.00 0.99
micro 0.99 0.98 0.98 0.98
macro 0.99 0.91 0.89 0.90
not-O 0.99 0.89 0.87 0.88
INFO:Entity level P/R/F1: 0.82/0.85/0.84
- Recurrent neural nets for NER
DEBUG:Token-level confusion matrix:
go\gu PER ORG LOC MISC O
PER 2987 32 47 12 71
ORG 136 1684 90 70 112
LOC 39 83 1907 21 44
MISC 43 45 47 1031 102
O 36 56 15 34 42618
DEBUG:Token-level scores:
label acc prec rec f1
PER 0.99 0.92 0.95 0.93
ORG 0.99 0.89 0.80 0.84
LOC 0.99 0.91 0.91 0.91
MISC 0.99 0.88 0.81 0.85
O 0.99 0.99 1.00 0.99
micro 0.99 0.98 0.98 0.98
macro 0.99 0.92 0.89 0.91
not-O 0.99 0.90 0.88 0.89
INFO:Entity level P/R/F1: 0.85/0.86/0.85
- Grooving with GRUs
DEBUG:Token-level confusion matrix:
go\gu PER ORG LOC MISC O
PER 2920 41 57 12 119
ORG 101 1716 73 64 138
LOC 22 95 1908 16 53
MISC 37 45 53 1017 116
O 21 67 14 39 42618
DEBUG:Token-level scores:
label acc prec rec f1
PER 0.99 0.94 0.93 0.93
ORG 0.99 0.87 0.82 0.85
LOC 0.99 0.91 0.91 0.91
MISC 0.99 0.89 0.80 0.84
O 0.99 0.99 1.00 0.99
micro 0.99 0.98 0.98 0.98
macro 0.99 0.92 0.89 0.90
not-O 0.99 0.91 0.88 0.89
INFO:Entity level P/R/F1: 0.86/0.85/0.85
- Easter Egg Hunt!
- Run
python q3_gru.py dynamicsto unfold your candy eggs
- Run
References
CS224n official website
Many code snippets come from