sentiment

.gitattributes

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README.md

@@ -12,11 +12,9 @@ license: mit
 
 # bert-base-multilingual-uncased-sentiment
 
-Visit the [NLP Town website](https://www.nlp.town) for an updated version of this model, with a 40% error reduction on product reviews.
+This a bert-base-multilingual-uncased model finetuned for sentiment analysis on product reviews in six languages: English, Dutch, German, French, Spanish and Italian. It predicts the sentiment of the review as a number of stars (between 1 and 5).
 
-This is a bert-base-multilingual-uncased model finetuned for sentiment analysis on product reviews in six languages: English, Dutch, German, French, Spanish, and Italian. It predicts the sentiment of the review as a number of stars (between 1 and 5).
-
-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.
+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.
 
 ## Training data
 
@@ -33,9 +31,9 @@ Here is the number of product reviews we used for finetuning the model:
 
 ## Accuracy
 
-The fine-tuned model obtained the following accuracy on 5,000 held-out product reviews in each of the languages:
+The finetuned model obtained the following accuracy on 5,000 held-out product reviews in each of the languages:
 
-- Accuracy (exact) is the exact match for the number of stars.
+- Accuracy (exact) is the exact match on the number of stars.
 - Accuracy (off-by-1) is the percentage of reviews where the number of stars the model predicts differs by a maximum of 1 from the number given by the human reviewer. 
 
 
@@ -50,8 +48,6 @@ The fine-tuned model obtained the following accuracy on 5,000 held-out product r
 
 ## Contact 
 
-In addition to this model, [NLP Town](http://nlp.town) offers custom models for many languages and NLP tasks.
-
-If you found this model useful, you can [buy us a coffee](https://www.buymeacoffee.com/yvespeirsman).
+In addition to this model, [NLP Town](https://www.nlp.town) offers custom, monolingual sentiment models for many languages and an improved multilingual model through [RapidAPI](https://rapidapi.com/nlp-town-nlp-town-default/api/multilingual-sentiment-analysis2/). 
 
 Feel free to contact us for questions, feedback and/or requests for similar models.

model.safetensors

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