Update README.md

README.md

@@ -27,17 +27,31 @@ should probably proofread and complete it, then remove this comment. -->
 # EstBERT128_Rubric
 
 This model is a fine-tuned version of [tartuNLP/EstBERT](https://huggingface.co/tartuNLP/EstBERT) on the rubric categories of the [Estonian Valence dataset](http://peeter.eki.ee:5000/valence/paragraphsquery).
-It achieves the following results on the evaluation set:
+The data was split into train/dev/test parts with 70/10/20 proportions.
+It achieves the following results on the test set:
 - Loss: 2.0552
 - Accuracy: 0.8329
 
 ## Model description
 
-More information needed
+A single linear layer classifier is fit on top of the last layer [CLS] token representation. The model is fully fine-tuned during training.
 
 ## Intended uses & limitations
 
-More information needed
+This model is intended to be used as it is. It can be used to predict nine rubric categories of Estonian texts. The nine rubric labels in the Estonian Valence dataset are:
+- ARVAMUS (opinion)
+- EESTI (domestic)
+- ELU-O (life)
+- KOMM-O-ELU (comments)
+- KOMM-P-EESTI (comments)
+- KRIMI (crime)
+- KULTUUR (culture)
+- SPORT (sports)
+- VALISMAA (world)
+
+It probably makes sense to treat the two comments categories (KOMM-O-ELU and KOMM-P-EESTI) as a single category.
+
+We do not guarantee that the model is useful for anything or that the predictions are accurate on new data.
 
 ## Training and evaluation data