Update README.md

README.md

@@ -25,12 +25,11 @@ MODEL = f"cardiffnlp/twitter-roberta-base-{task}"
 tokenizer = AutoTokenizer.from_pretrained(MODEL)
 
 # download label mapping
-labels=[]
 mapping_link = f"https://raw.githubusercontent.com/cardiffnlp/tweeteval/main/datasets/{task}/mapping.txt"
 with urllib.request.urlopen(mapping_link) as f:
     html = f.read().decode('utf-8').split("\n")
-    spamreader = csv.reader(html[:-1], delimiter='\t')
-labels = [row[1] for row in spamreader]
+    spamreader = csv.reader(html, delimiter='\t')
+labels = [row[1] for row in spamreader if len(row) > 1]
 
 # PT
 model = AutoModelForSequenceClassification.from_pretrained(MODEL)
@@ -64,24 +63,8 @@ for i in range(scores.shape[0]):
 Output: 
 
 ```
-1) 😘 0.2637
-2) ❤️ 0.1952
-3) 💕 0.1171
-4) ✨ 0.0927
-5) 😊 0.0756
-6) 💜 0.046
-7) 💙 0.0444
-8) 😍 0.0272
-9) 😉 0.0228
-10) 😎 0.0198
-11) 😜 0.0166
-12) 😂 0.0132
-13) 😁 0.0131
-14) ☀ 0.0112
-15) 🎄 0.009
-16) 💯 0.009
-17) 🔥 0.008
-18) 📷 0.0057
-19) 🇺🇸 0.005
-20) 📸 0.0048
+1) joy 0.9061
+2) optimism 0.0407
+3) sadness 0.0406
+4) anger 0.0126
 ```