Update README.md

README.md

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 ### Model Overview:
-This NLP model is fine-tuned with a focus on analyzing sentiment in financial text and news headlines. It was trained using the [bert-base-uncased](https://huggingface.co/bert-base-uncased) model on the [financial_phrasebank](https://huggingface.co/datasets/financial_phrasebank) and [auditor_sentiment](https://huggingface.co/datasets/FinanceInc/auditor_sentiment) datasets.
+This NLP model is fine-tuned with a focus on analyzing sentiment in financial text and news headlines. It was fine-tuned using the [bert-base-uncased](https://huggingface.co/bert-base-uncased) model on the [financial_phrasebank](https://huggingface.co/datasets/financial_phrasebank) and [auditor_sentiment](https://huggingface.co/datasets/FinanceInc/auditor_sentiment) datasets.
 
-**Accuracies:**
+**Accuracies:**\
 **financial_phrasebank accuracy:** 0.993\
-**auditor_senitment accuracy:** 0.974\
+**auditor_senitment accuracy:** 0.974
 
 ### Training Hyperparameters:
 
@@ -25,7 +25,7 @@ This NLP model is fine-tuned with a focus on analyzing sentiment in financial te
 **Optimizer:** AdamW-betas(0.9, 0.999)\
 **Learning Rate Scheduler:** Linear\
 **Number of Epochs:** 6\
-**Number of Warmup Steps:** 0.2 * Number of Training Steps\
+**Number of Warmup Steps:** 0.2 * Number of Training Steps
 
 ### How To Use: