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@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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  # distilbert-base-uncased-finetuned-mnli-amazon-query-shopping
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  This model is a fine-tuned version of [nlptown/bert-base-multilingual-uncased-sentiment](https://huggingface.co/nlptown/bert-base-multilingual-uncased-sentiment?text=I+like+you.+I+love+you) on an [Amazon US Customer Reviews Dataset](https://www.kaggle.com/datasets/cynthiarempel/amazon-us-customer-reviews-dataset). The code for the fine-tuning process can be found
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- [here](https://github.com/vanderbilt-data-science/bigdata). This model is uncased: it does
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  not make a difference between english and English.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.5202942490577698
 
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  # distilbert-base-uncased-finetuned-mnli-amazon-query-shopping
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  This model is a fine-tuned version of [nlptown/bert-base-multilingual-uncased-sentiment](https://huggingface.co/nlptown/bert-base-multilingual-uncased-sentiment?text=I+like+you.+I+love+you) on an [Amazon US Customer Reviews Dataset](https://www.kaggle.com/datasets/cynthiarempel/amazon-us-customer-reviews-dataset). The code for the fine-tuning process can be found
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+ [here](https://github.com/vanderbilt-data-science/bigdata/blob/main/06-fine-tune-BERT-on-our-dataset.ipynb). This model is uncased: it does
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  not make a difference between english and English.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.5202942490577698