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fine-tuned-distilbert-base-uncased

Text Classification

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naveedui commited on May 13

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@@ -10,7 +10,7 @@ model-index:
 This model is a fine-tuned version of distilbert-base-uncased, tailored specifically for sentiment analysis. DistilBERT, a distilled version of the more complex BERT model, offers a good balance between performance and resource efficiency, making it ideal for environments where computational resources are limited.
-Purpose
 The primary purpose of this fine-tuned model is to perform sentiment analysis on English movie reviews. It classifies text into positive or negative sentiments based on the content of the review. This model has been trained and evaluated on a subset of the IMDb reviews dataset, making it particularly well-suited for analyzing movie review sentiments.
 # results

 This model is a fine-tuned version of distilbert-base-uncased, tailored specifically for sentiment analysis. DistilBERT, a distilled version of the more complex BERT model, offers a good balance between performance and resource efficiency, making it ideal for environments where computational resources are limited.
+Purpose:
 The primary purpose of this fine-tuned model is to perform sentiment analysis on English movie reviews. It classifies text into positive or negative sentiments based on the content of the review. This model has been trained and evaluated on a subset of the IMDb reviews dataset, making it particularly well-suited for analyzing movie review sentiments.
 # results