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# distilbert-base-uncased-finetuned-mnli-amazon-query-shopping
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This model is a fine-tuned version of [
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[here](https://github.com/vanderbilt-data-science/
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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.
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- Accuracy: 0.
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## Model description
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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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- Accuracy: 0.8
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## Model description
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