Update README.md

README.md

@@ -4,13 +4,13 @@ license: mit
 
 # Model Card for BERT hate offensive tweets
 
-BERT base uncased trained on the data that can be found here: MartynaKopyta/hate_offensive_tweets (https://huggingface.co/datasets/MartynaKopyta/hate_offensive_tweets) to classify tweets as 0 - hate, 1 - offensive or 2 - neither.
+BERT base uncased trained on the data that can be found here: [MartynaKopyta/hate_offensive_tweets](https://huggingface.co/datasets/MartynaKopyta/hate_offensive_tweets) to classify tweets as 0 - hate, 1 - offensive or 2 - neither.
 
-You can find the notebook used for training in my GitHub repo: MartynaKopyta/BERT_FINE-TUNING (https://github.com/MartynaKopyta/BERT_FINE-TUNING/blob/main/BERT_hate_offensive_speech.ipynb).
+You can find the notebook used for training in my GitHub repo: [MartynaKopyta/BERT_FINE-TUNING](https://github.com/MartynaKopyta/BERT_FINE-TUNING/blob/main/BERT_hate_offensive_speech.ipynb).
 
 ## Model Details
 
-- **Finetuned from model bert-base-uncased:https://huggingface.co/bert-base-uncased** 
+- **Finetuned from model [bert-base-uncased](https://huggingface.co/bert-base-uncased)** 
 
 
 ## Bias, Risks, and Limitations
@@ -19,12 +19,12 @@ The dataset was not big enough for BERT to learn to classify 3 classes accuratel
 
 
 ## How to Get Started with the Model
-
+```
 from transformers import AutoModelForSequenceClassification, AutoTokenizer
 
 model = AutoModelForSequenceClassification.from_pretrained('MartynaKopyta/BERT_hate_offensive_tweets')
 tokenizer = AutoTokenizer.from_pretrained('MartynaKopyta/BERT_hate_offensive_tweets')
-
+```
 
 #### Training Hyperparameters
 
@@ -33,9 +33,11 @@ tokenizer = AutoTokenizer.from_pretrained('MartynaKopyta/BERT_hate_offensive_twe
 - **epochs:3**
 
 ## Evaluation
-
+```
 Accuracy: 0.779373368146214
+
 Classification Report:
+
               precision    recall  f1-score   support
 
            0       0.74      0.68      0.71      1532
@@ -51,4 +53,5 @@ Confusion Matrix:
  [ 169 1343   20]
  [ 204  132 1196]]
 
-MCC: 0.670
+MCC: 0.670
+```