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@@ -16,6 +16,8 @@ This is a bert-base-multilingual-uncased model finetuned for sentiment analysis
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  This model is intended for direct use as a sentiment analysis model for product reviews in any of the six languages above or for further finetuning on related sentiment analysis tasks.
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  ## Training data
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  Here is the number of product reviews we used for finetuning the model:
@@ -48,8 +50,8 @@ The fine-tuned model obtained the following accuracy on 5,000 held-out product r
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  ## Contact
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- If you found this model useful, you can buy me a coffee at https://www.buymeacoffee.com/yvespeirsman.
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  In addition to this model, [NLP Town](http://nlp.town) offers custom models for many languages and NLP tasks.
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- Feel free to contact me for questions, feedback and/or requests for similar models.
 
 
 
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  This model is intended for direct use as a sentiment analysis model for product reviews in any of the six languages above or for further finetuning on related sentiment analysis tasks.
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+ NLP Town also offers an newer model based on ModernBert, with a 40% error reduction on product reviews. Find all the details [on our website](https://www.nlp.town).
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  ## Training data
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  Here is the number of product reviews we used for finetuning the model:
 
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  ## Contact
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  In addition to this model, [NLP Town](http://nlp.town) offers custom models for many languages and NLP tasks.
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+ If you found this model useful, you can [buy us a coffee](https://www.buymeacoffee.com/yvespeirsman).
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+ Feel free to contact us for questions, feedback and/or requests for similar models.