Update README.md

Some more... Extra text.

README.md

@@ -20,6 +20,8 @@ It achieves the following results on the evaluation set:
 - Loss: 0.7241
 
 ## Model description
+This is how to use the model with the transformer library to do a text classification task.
+This model was trained and built for sentiment analysis with a text classification model architecture.
 ```python
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 from transformers import pipeline
@@ -72,7 +74,7 @@ The following hyperparameters were used during training:
 
 ### Training results
 ```python
-{training_loss=0.3821827131159165}
+{'training_loss'=0.3821827131159165}
 
 {'train_runtime': 174.1546, 'train_samples_per_second': 93.509,
 'train_steps_per_second': 5.857, 'total_flos': 351397804992312.0,