Update README.md

README.md

@@ -36,25 +36,32 @@ More information needed
 
 Evaluation: https://github.com/frank-morales2020/MLxDL/blob/main/FineTunning_Testing_For_EmotionQADataset.ipynb
 
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+*************
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 The following hyperparameters were used during training:
 learning_rate: 0.0002 train_batch_size: 3 eval_batch_size: 8 seed: 42 gradient_accumulation_steps: 2 total_train_batch_size: 6 optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 lr_scheduler_type: constant lr_scheduler_warmup_ratio: 0.03
 num_epochs: 1
 
-NOTE: test - Accuracy (Eval dataset and predict) for a sample of 2000: 59.45%
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+Accuracy (Eval dataset and predict) for a sample of 2000: 59.45%
+
+*************
 
 The following hyperparameters were used during training:
 learning_rate: 0.0002 train_batch_size: 3 eval_batch_size: 8 seed: 42 gradient_accumulation_steps: 2 total_train_batch_size: 6 optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 lr_scheduler_type: constant lr_scheduler_warmup_ratio: 0.03
 num_epochs: 25
 
-NOTE: test - Accuracy (Eval dataset and predict) for a sample of 2000: 79.95%
+Accuracy (Eval dataset and predict) for a sample of 2000: 79.95%
+
+*************
 
 The following hyperparameters were used during training:
 learning_rate: 0.0002 train_batch_size: 3 eval_batch_size: 8 seed: 42 gradient_accumulation_steps: 2 total_train_batch_size: 6 optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 lr_scheduler_type: constant lr_scheduler_warmup_ratio: 0.03
 num_epochs: 40
 
-NOTE: test - Accuracy (Eval dataset and predict) for a sample of 2000: 80.70%
+ Accuracy (Eval dataset and predict) for a sample of 2000: 80.70%
+
+*************
 
 ## Training procedure