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README.md

@@ -21,8 +21,8 @@ license: cc-by-4.0
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 # roberta-base for QA
 
-objective:
-  This is Roberta Base with Domain Adaptive Pretraining on Movie Corpora --> Then trained for the NER task using MIT Movie Dataset --> Then a changed head to do the SQuAD Task. This makes a QA model capable of answering questions in the movie domain, with additional information coming from a different task (NER - Task Transfer). 
+Objective:
+  This is Roberta Base with Domain Adaptive Pretraining on Movie Corpora --> Then trained for the NER task using MIT Movie Dataset --> Then a changed head to do the SQuAD Task. This makes a QA model capable of answering questions in the movie domain, with additional information coming from a different task (NER - Task Transfer).  
   https://huggingface.co/thatdramebaazguy/movie-roberta-base was used as the MovieRoberta.
   
 ```
@@ -34,25 +34,25 @@ pipeline(model=model_name, tokenizer=model_name, revision="v1.0", task="question
 **Language model:** roberta-base  
 **Language:** English  
 **Downstream-task:** NER --> QA  
-**Training data:** imdb, polarity movie data, cornell_movie_dialogue, 25mlens movie names, MIT Movie, SQuADv1
-**Eval data:** MoviesQA (From https://github.com/ibm-aur-nlp/domain-specific-QA) 
+**Training data:** imdb, polarity movie data, cornell_movie_dialogue, 25mlens movie names, MIT Movie, SQuADv1  
+**Eval data:** MoviesQA (From https://github.com/ibm-aur-nlp/domain-specific-QA)  
 **Infrastructure**: 4x Tesla v100   
 **Code:**  See [example](https://github.com/adityaarunsinghal/Domain-Adaptation/blob/master/scripts/shell_scripts/movieR_NER_squad.sh)    
 
 ## Hyperparameters
 ```
-Num examples = 88567
-Num Epochs = 3
-Instantaneous batch size per device = 32
-Total train batch size (w. parallel, distributed & accumulation) = 128
+Num examples = 88567  
+Num Epochs = 3  
+Instantaneous batch size per device = 32  
+Total train batch size (w. parallel, distributed & accumulation) = 128  
 
 ``` 
 ## Performance
 
 ### Eval on MoviesQA
-eval_samples =   10790
-2021-05-07 21:48:01,204 >>   exact_match  = 83.0274
-2021-05-07 21:48:01,204 >>   f1           = 90.1615
+- eval_samples =   10790  
+- 2021-05-07 21:48:01,204 >>   exact_match  = 83.0274  
+- 2021-05-07 21:48:01,204 >>   f1           = 90.1615  
 
 Github Repo: 
 - [Domain-Adaptation Project](https://github.com/adityaarunsinghal/Domain-Adaptation/)