Update README.md

README.md

@@ -30,8 +30,8 @@ Transformer model with linear sequence classification head, trained with cross-e
 - **Developed by:** James Kelly
 - **Model type:** SequenceClassification
 - **Language(s) (NLP):** English
-- **License:** [MIT]
-- **Finetuned from model:** [allenai/scibert_scivocab_uncased]
+- **License:** MIT
+- **Finetuned from model:** `allenai/scibert_scivocab_uncased`
 
 ### Model Sources 
 
@@ -69,14 +69,15 @@ though this is still an important clinical task.
 
 Use the code below to get started with the model.
 
-'''
+'
+
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
 tokenizer = AutoTokenizer.from_pretrained("semaj83/scibert_finetuned_ctmatch")
 
 model = AutoModelForSequenceClassification.from_pretrained("semaj83/scibert_finetuned_ctmatch")
 
-'''
+'
 
 ## Training Details
 
@@ -120,6 +121,7 @@ early_stopping=True
 sklearn classifier table on random test split:
 
 `
+
                 precision    recall  f1-score   support
 
            0       0.88      0.93      0.90      5430
@@ -130,6 +132,7 @@ sklearn classifier table on random test split:
    macro avg       0.70      0.66      0.67      7939
 weighted avg       0.79      0.80      0.79      7939
 
+
 `