Update README.md

README.md

@@ -143,8 +143,7 @@ Implementations of SacreBLEU, BERT Score, ROUGLE, METEOR, and SARI are from Hugg
 
 ## Results 
 
-We tested our model on the SAS test set (200 samples). We generate 10 lay summaries based on each sample's abstract. During generation, we used top-p sampling with $p=0.9$.
-The mean performance is reported below.
+We tested our model on the SAS test set (200 samples). We generate 10 lay summaries based on each sample's abstract. During generation, we used top-p sampling with p=0.9. The mean performance is reported below.
 
 
 | Metrics        | SAS               |
@@ -157,7 +156,7 @@ The mean performance is reported below.
 | METEOR↑        | 43.75             |
 | SARI↑          | 51.96             |
 | ARI↓           | 17.04             |
-Note: 1. Some generated texts are too short (less than 100 words) to calcualte meaningful ARI. We therefore concatenated adjecent five texts and compute ARI for the 400 longer texts (instead of original 2,000 texts). 2. BERT score, ROUGE, and METEOR multiplied by 100.
+Note: 1. Some generated texts are too short (less than 100 words) to calcualte meaningful ARI. We therefore concatenated adjecent five texts and compute ARI for the 400 longer texts (instead of original 2,000 texts). 2. BERT score, ROUGE, and METEOR are multiplied by 100.
 
 
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