add performance info

README.md

@@ -1,8 +1,23 @@
 ## BabyBERTA
 
-BabyBERTA is a slightly-modified and much smaller RoBERTa model trained on 5M words of American-English child-directed input.
+### Overview
+
+BabyBERTA is a light-weight version of RoBERTa trained on 5M words of American-English child-directed input.
 It is intended for language acquisition research, on a single desktop with a single GPU - no high-performance computing infrastructure needed. 
 
+### Performance
+
+The provided model is the best-performing out of 10 that were evaluated on the [Zorro](https://github.com/phueb/Zorro) test suite.
+This model was trained for 400K steps, and achieves an overall accuracy of 80.3,
+ comparable to RoBERTa-base, which achieves an overall accuracy of 82.6 on the latest version of Zorro (as of October, 2021).
+The latter value is slightly larger than that reported in the paper (Huebner et al., 2020) because the authors previously lower-cased all words in Zorro before evaluation.
+Lower-casing of proper nouns is detrimental to RoBERTa-base because RoBERTa-base has likely been exposed to proper nouns that are title-cased.
+Because BabyBERTa is not case-sensitive, performance is not influenced by this change.
+ 
+
+
+### Additional Information
+
 This model was trained by [Philip Huebner](https://philhuebner.com), currently at the [UIUC Language and Learning Lab](http://www.learninglanguagelab.org).
 
 More info can be found [here](https://github.com/phueb/BabyBERTa).