Update README.md

README.md

@@ -18,14 +18,21 @@ The model is intended to identify skepticism of COVID-19 policies (i.e. masks, s
 
 It's a pretty simple task but I used a grid search to optimize hyperparameters. The final model is achieves the following results and uses the following hyperparamters: 
 
-{'train_runtime': 174.3258, 'train_samples_per_second': 18.896, 'train_steps_per_second': 2.375, 'train_loss': 0.1576320076910194, 'epoch': 6.0}
-{'eval_loss': 0.8522606492042542, 'eval_runtime': 3.8368, 'eval_samples_per_second': 70.111, 'eval_steps_per_second': 8.862, 'epoch': 6.0}
+- 'train_runtime': 174.3258
+- 'train_samples_per_second': 18.896
+- 'train_steps_per_second': 2.375
+- 'train_loss': 0.1576320076910194
+- 'eval_loss': 0.8522606492042542
+- 'eval_runtime': 3.8368
+- 'eval_samples_per_second': 70.111
+- 'eval_steps_per_second': 8.862
+- 'epoch': 6.0
 
 Optimized Hyperparameters
 ----------------------------------------------------------------------------------------------------
-The best learning rate is: 5.4761828368201554e-05
-The best weight decay is: 0.0003655991822889909
-The best epoch is : 6
-The best train split is : 0.3284489429375188
+- The best learning rate is: 5.4761828368201554e-05
+- The best weight decay is: 0.0003655991822889909
+- The best epoch is : 6
+- The best train split is : 0.3284489429375188