Update README.md

README.md

@@ -22,7 +22,7 @@ This is a token classification model using BERT base uncased as the base model.
 The model is fine-tuned on the (QueryNER training dataset)[https://huggingface.co/datasets/bltlab/queryner]. 
 
 
-- **Developed by:** (BLT Lab)[https://github.com/bltlab] in collaboration with eBay.
+- **Developed by:** [BLT Lab](https://github.com/bltlab) in collaboration with eBay.
 - **Funded by:** eBay
 - **Shared by:** (@cpalenmichel)[https://github.com/cpalenmichel]
 - **Model type:** Token Classification / Sequence Labeling / Chunking
@@ -32,9 +32,9 @@ The model is fine-tuned on the (QueryNER training dataset)[https://huggingface.c
 
 ### Model Sources
 
-Underlying model is based on (BERT base-uncased)[https://huggingface.co/google-bert/bert-base-uncased]. 
+Underlying model is based on [BERT base-uncased](https://huggingface.co/google-bert/bert-base-uncased). 
 
-- **Repository:** (https://github.com/bltlab/query-ner)[https://github.com/bltlab/query-ner]
+- **Repository:** [https://github.com/bltlab/query-ner](https://github.com/bltlab/query-ner)
 - **Paper:** Accepted at LREC-COLING Coming soon
 
 ## Uses
@@ -79,13 +79,13 @@ See paper for details.
 ## Evaluation
 
 Evaluation details provided in the paper. 
-Scoring was done using (SeqScore)[https://github.com/bltlab/seqscore] using the conlleval repair method for invalid label transition sequences. 
+Scoring was done using [SeqScore](https://github.com/bltlab/seqscore) using the conlleval repair method for invalid label transition sequences. 
 
 ### Testing Data, Factors & Metrics
 
 #### Testing Data
 
-QueryNER test set: (https://huggingface.co/datasets/bltlab/queryner)[https://huggingface.co/datasets/bltlab/queryner]
+QueryNER test set: [https://huggingface.co/datasets/bltlab/queryner](https://huggingface.co/datasets/bltlab/queryner)
 
 
 #### Factors