Updated model description

README.md

@@ -27,11 +27,11 @@ A fine-tuned RoBERTa model designed for an Natural Language Inference (NLI) task
 
 This model builds upon the roberta-base architecture, adding a multi-layer classification head for NLI. It computes average pooled representations of premise and hypothesis tokens (identified via `token_type_ids`) and concatenates them before passing through additional linear and non-linear layers. The final output is used to classify the pair of sentences into one of three classes.
 
-- **Developed by:** {{ Dev Soneji}}
-- **Language(s):** {{ English}}
-- **Model type:** {{ model_type | default("[More Information Needed]", true)}}
-- **Model architecture:** {{ RoBERTa encoder with a multi-layer classification head}}
-- **Finetuned from model:** {{ roberta-base }}
+- **Developed by:** Dev Soneji and Patrick Mermelstein Lyons
+- **Language(s):** English
+- **Model type:** Supervised
+- **Model architecture:** RoBERTa encoder with a multi-layer classification head
+- **Finetuned from model:** roberta-base 
 
 ### Model Resources