Minor update.

README.md

@@ -24,7 +24,7 @@ It achieves the following results on the evaluation set:
 
 ## Model description
 
-This latest variation of the OME is a text classifier based on fine tuned with 47 categories for classifying emotion in English language examples from a curated dataset deriving emotional clusters using dimensions of Subjectivity, Relativity, and Generativity. Additional dimensions of Clarity and Acceptance were used to map seven population clusters of ontological experiences categorized as Trust or Love, Happiness or Pleasure, Sadness or Trauma, Anger or Disgust, Fear or Anxiety, Guilt or Shame, and Jealousy or Envy.
+This latest variation of the OME is a text classifier based on distilroberta and fine tuned with 47 categories for classifying emotion in English language examples from a curated dataset deriving emotional clusters using dimensions of Subjectivity, Relativity, and Generativity. Additional dimensions of Clarity and Acceptance were used to map seven population clusters of ontological experiences categorized as Trust or Love, Happiness or Pleasure, Sadness or Trauma, Anger or Disgust, Fear or Anxiety, Guilt or Shame, and Jealousy or Envy.
 
 ## Intended uses & limitations
 
@@ -118,7 +118,7 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Use OptimizerNames.ADAMW\_TORCH\_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer\_args=No additional optimizer arguments
 - lr\_scheduler\_type: linear
-- num_epochs: 30.0
+- num\_epochs: 30.0
 
 ### Training results