Update README.md

README.md

@@ -7,6 +7,9 @@ tags:
 model-index:
 - name: RoBERTa_Sentiment_Analysis
   results: []
+language:
+- en
+pipeline_tag: text-classification
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -28,21 +31,28 @@ More information needed
 
 ## Training and evaluation data
 
-'train.csv' of Twitter Sentiment Analysis is used for training and evaluation
+'train.csv' of Twitter Sentiment Analysis is split into training and evaluation sets (80-20)
 
 ## Training procedure
 
+Pretrained RobertaTokenizerFast is used for tokenizing preprocessed data
+
+Pretrained RobertaForSequenceClassification is used as the classification model
+
+Hyperparameters are defined in TrainingArguments and Trainer is used to train the model
+
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
 - train_batch_size: 50
 - eval_batch_size: 50
-- seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
 - num_epochs: 5
+- weight_decay : 0.0000001
+- report_to="tensorboard"
 
 ### Training results