Create README.md

README.md

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+Results after training in 80% of 15189 instances 
+
+20it [00:11, 1.85it/s]Train: wpb=2121, num_updates=20, accuracy=44.1, loss=0.00
+50it [00:28, 1.76it/s]Train: wpb=2121, num_updates=50, accuracy=55.4, loss=0.00
+100it [00:55, 1.88it/s]Train: wpb=2117, num_updates=100, accuracy=64.5, loss=0.00
+200it [01:48, 1.85it/s]Train: wpb=2132, num_updates=200, accuracy=71.6, loss=0.00
+300it [02:42, 1.88it/s]Train: wpb=2147, num_updates=300, accuracy=75.1, loss=0.00
+380it [03:24, 1.86it/s]
+Train: wpb=2142, num_updates=380, accuracy=76.9, loss=0.00
+| epoch 000 | train accuracy=76.9%, train loss=0.00
+| epoch 000 | valid accuracy=85.7%, valid loss=0.00\
+
+20it [00:10, 1.85it/s]Train: wpb=2121, num_updates=20, accuracy=84.6, loss=0.00
+50it [00:27, 1.77it/s]Train: wpb=2121, num_updates=50, accuracy=84.6, loss=0.00
+100it [00:54, 1.87it/s]Train: wpb=2117, num_updates=100, accuracy=85.1, loss=0.00
+200it [01:47, 1.86it/s]Train: wpb=2132, num_updates=200, accuracy=85.4, loss=0.00
+300it [02:41, 1.88it/s]Train: wpb=2147, num_updates=300, accuracy=85.6, loss=0.00
+380it [03:24, 1.86it/s]
+Train: wpb=2142, num_updates=380, accuracy=85.8, loss=0.00
+| epoch 001 | train accuracy=85.8%, train loss=0.00
+| epoch 001 | valid accuracy=88.3%, valid loss=0.00
+
+
+You can evaluate the performance of our model by writing the following example:
+"google chrome before 18. 0. 1025. 142 does not properly validate the renderer's navigation requests, which has unspecified impact and remote attack vectors."
+
+The result should be similar to:
+['B-vendor', 'B-application', 'B-version', 'I-version', 'I-version', 'I-version', 'I-version', 'I-version', 'I-version', 'I-version', 'I-version', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'B-relevant_term', 'O', 'O', 'O', 'O', 'O', 'O', 'B-relevant_term', 'B-relevant_term', 'O', 'O']