Update README.md

README.md

@@ -16,7 +16,7 @@ It achieves the following results on the evaluation set:
 - F1 Score: 0.686
 
 ## Model description
-The model takes procurement descriptions written in any of [104 languages](https://github.com/google-research/bert/blob/master/multilingual.md#list-of-languages) and classifies into 45 sector classes represented by [CPV(Common Procurement Vocabulary)](https://simap.ted.europa.eu/en_GB/web/simap/cpv) code descriptions.
+The model takes procurement descriptions written in any of [104 languages](https://github.com/google-research/bert/blob/master/multilingual.md#list-of-languages) and classifies them into 45 sector classes represented by [CPV(Common Procurement Vocabulary)](https://simap.ted.europa.eu/en_GB/web/simap/cpv) code descriptions as listed below.
 
  | Common Procurement Vocabulary |
  |:-----------------------------|
@@ -67,10 +67,15 @@ The model takes procurement descriptions written in any of [104 languages](https
  | Transport services (excl. Waste transport). 💺
 
 ## Intended uses & limitations
-More information needed
+Input description should be written in any of [the 104 languages](https://github.com/google-research/bert/blob/master/multilingual.md#list-of-languages) that MBERT supports.
+
 ## Training and evaluation data
-More information needed
+The whole data consists of 744,360 rows. Shuffled and split into train and validation sets by using 80%/20% manner.
+Each description represents a unique contract notice description awarded between 2011 and 2018.
+Both training and validation data have contract notice descriptions written in 22 European Languages. (Malta and Irish are extracted due to scarcity compared to whole data)
+
 ## Training procedure
+The training procedure has been completed on Google Cloud V3-8 TPUs. Thanks [Google](https://sites.research.google/trc/about/) for giving the access to Cloud TPUs
 
 ### Training hyperparameters
 The following hyperparameters were used during training: