Update README.md

README.md

@@ -15,6 +15,32 @@ widget:
 - text: "Jean Paul Gaultier Classique - 50 ML Eau de Parfum  Damen Parfum"
 ---
 
+## What is YODA
+
+YODA is a series of models for Google Feed product optimization. We aim to increase the market reach for ecommerce augmenting and improving certain metadata like short titles, colors, measures and more. YODA is being used in production by +300 companies with +3.5M products.
+
+## What we use NER for
+
+We have trained a NER model for product feature extraction. We retrieve data like colors, sizes, brands and energy labels. Trained with +3M lines of product metadata, the model returns the next scores:
+
+Results:
+- F-score (micro) 0.972
+- F-score (macro) 0.9692
+- Accuracy 0.9461
+
+By class:
+              precision    recall  f1-score   support
+
+        size     0.9734    0.9793    0.9764     26707
+       brand     0.9618    0.9788    0.9702     15621
+       color     0.9566    0.9612    0.9589      6785
+      energy     0.9444    1.0000    0.9714       119
+
+   micro avg     0.9673    0.9767    0.9720     49232
+   macro avg     0.9591    0.9798    0.9692     49232
+weighted avg     0.9674    0.9767    0.9720     49232
+
+
 ### Demo: How to use in Flair
 Requires:
 - **[Flair](https://github.com/flairNLP/flair/)** (`pip install flair`)
@@ -41,4 +67,8 @@ print('The following NER tags are found:')
 # iterate over entities and print
 for entity in sentence.get_spans('ner'):
     print(entity)
-```
+```
+
+## Contact
+
+You may contact the lead ML developer [Iván R. Gázquez](mailto:ivan@gazquez.com)