Update README.md

README.md

@@ -13,26 +13,19 @@ probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [vinai/bertweet-covid19-base-uncased](https://huggingface.co/vinai/bertweet-covid19-base-uncased) on a dataset of 10k tweets about COVID-19 policies from US legislators in the House and Senate. 
 
-The model is intended to identify skepticism (label == 1) of COVID-19 policies (i.e. masks, social distancing, lockdowns, vaccines etc.). 
+The model is intended to identify skepticism of COVID-19 policies (i.e. masks, social distancing, lockdowns, vaccines etc.). 
 
 
-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
-- 'eval_loss': 0.8522606492042542
-- 'eval_runtime': 3.8368
-- 'eval_samples_per_second': 70.111
-- 'eval_steps_per_second': 8.862
-- 'epoch': 6.0
+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: 
 
 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: 9.928559980965476e-06
+The best weight decay is: 0.003083325125091835
+The best epoch is : 5
+The best train split is : 0.2864649363822965
+
+