Update README.md

README.md

@@ -15,16 +15,14 @@ widget:
 ## This model is trained for GoEmotions dataset which contains labeled 58k Reddit comments with 28 emotions
 - admiration, amusement, anger, annoyance, approval, caring, confusion, curiosity, desire, disappointment, disapproval, disgust, embarrassment, excitement, fear, gratitude, grief, joy, love, nervousness, optimism, pride, realization, relief, remorse, sadness, surprise + neutral
 
-
-## The training script is provided here: https://github.com/bsinghpratap/roberta_train_goEmotion
+## Training details:
+- The training script is provided here: https://github.com/bsinghpratap/roberta_train_goEmotion
 - The model works well on most of the emotions except: 'desire', 'disgust', 'embarrassment', 'excitement', 'fear', 'grief', 'nervousness', 'pride', 'relief', 'remorse', 'surprise']
 - I'll try to fine-tune the model further and update here if RoBERTa achieves a better performance.
-
-## Some Training details:
 - Each text datapoint can have more than 1 label. Most of the training set had 1 label: Counter({1: 36308, 2: 6541, 3: 532, 4: 28, 5: 1})
-- So currently I just used the first label for each of the datapoint. Not ideal but it does a decent job.
+-- So currently I just used the first label for each of the datapoint. Not ideal but it does a decent job.
 
-## Current Performance
+## Model Performance
 ============================================================<br>
 Emotion: admiration<br>
 ============================================================<br>