Update README.md

README.md

@@ -36,7 +36,7 @@ A sequence of word embeddings is therefore processed sequentially by each transf
 
 ## Details model architecture
 
-The *conventional* T5 architectures are summarized in the following table.
+The *conventional* T5 architectures are summarized in the following table:
 
 | Model | nl | ff | dm | kv | nh | #Params|
 | ----| ---- | ---- | ---- | ---- | ---- | ----|
@@ -48,7 +48,17 @@ The *conventional* T5 architectures are summarized in the following table.
 | **XL** | **24/24** | **16384** | **1024** | **128** | **32** | **3B**|
 | XXL | 24/24 | 65536 | 1024 | 128 | 128 | 11B|
 
-This 
+with the following definitions:
+
+| NL | Number of transformer blocks (depth) | 
+| EL | Number of transformer blocks in the encoder (encoder depth) | 
+| DL | Number of transformer blocks in the decoder (decoder depth) | 
+| DM | Dimension of embedding vector (output vector of transformers block) | 
+| KV | Dimension of key/value projection matrix | 
+| NH | Number of attention heads | 
+| FF | Dimension of intermediate vector within transformer block (size of feed-forward projection matrix) | 
+| SH | Signifies that attention heads are shared | 
+| SKV | Signifies that key-values projection matrices are tied | 
 
 ## Pre-Training