Update README.md

README.md

@@ -98,6 +98,8 @@ Masked Language Modeling objective with 15% masked token ratio.
 ### Preprocessing
 
 Tokenize `data["train"]["fen"]` with max-length padding to 200 tokens with default `distilbert-base-cased` tokenizer. 
+Inefficient: Most of the vocab is never observed in FEN, wasting embedding parameters. 
+The sequence length / pos embedding size of model and sequence length of data preprocessing leads to lots of padding and wasted parameters. FENs should be shorter than 90 characters.
 Experiments with reduced max-length in tokenization show performance gains.
 
 ### Speeds, Sizes, Times