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Update README.md

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@@ -15,6 +15,8 @@ library_name: transformers
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  safetensors: true
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  ---
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  ### Training Details
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  The model was trained on the McAuley-Lab/Amazon-Reviews-2023 dataset. This dataset contains labeled customer reviews from Amazon, focusing on two primary categories: Positive and Negative.
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@@ -37,4 +39,11 @@ Precision: 0.98
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  Recall: 0.99
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- F1-Score: 0.98
 
 
 
 
 
 
 
 
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  safetensors: true
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  ---
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+ ### sentiment_mapping = {1: "Negative", 0: "Positive"}
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+
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  ### Training Details
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  The model was trained on the McAuley-Lab/Amazon-Reviews-2023 dataset. This dataset contains labeled customer reviews from Amazon, focusing on two primary categories: Positive and Negative.
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  Recall: 0.99
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+ F1-Score: 0.98
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+
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+ ```python
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+ from transformers import pipeline
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+
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+ classifier = pipeline("text-classification", model="dnzblgn/Sentiment-Analysis-Customer-Reviews")
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+ result = classifier("The product didn't arrive on time and was damaged.")
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+ print(result)