Update README.md

README.md

@@ -21,11 +21,16 @@ Question: Where is the user flying from?
 Answer  : (empty)
 ```
 
-Thus, by asking questions for each intent and slot in natural language, we can effectively construct an NLU hypothesis. For more details,
-please read the paper: 
-[Language model is all you need: Natural language understanding as question answering](https://assets.amazon.science/33/ea/800419b24a09876601d8ab99bfb9/language-model-is-all-you-need-natural-language-understanding-as-question-answering.pdf).
+Thus, by asking questions for each intent and slot in natural language, we can effectively construct an NLU hypothesis. For more details, please read the paper: [Language model is all you need: Natural language understanding as question answering](https://assets.amazon.science/33/ea/800419b24a09876601d8ab99bfb9/language-model-is-all-you-need-natural-language-understanding-as-question-answering.pdf).
 
-To see how to train a QANLU model, visit the [Amazon Science repository](https://github.com/amazon-research/question-answering-nlu)
+## Model training
+
+Instructions for how to train and evaluate a QANLU model, as well as the necessary code for ATIS are in the [Amazon Science repository](https://github.com/amazon-research/question-answering-nlu).
+
+## Intended use and limitations
+
+This model has been fine-tuned on ATIS (English) and is intended to demonstrate the power of this approach. For other domains or tasks, it should be further fine-tuned 
+on relevant data.
 
 ## Use in transformers:
 
@@ -53,4 +58,9 @@ If you use this work, please cite:
 
 ## License
 
-This library is licensed under the CC BY NC License.
+This library is licensed under the CC BY NC License.
+
+---
+license: "cc-by-nc"
+datasets:
+  -atis