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README.md
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# deberta-v3-base-finetuned-finance-text-classification
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.7687
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- Accuracy: 0.8913
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license: mit
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tags:
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- generated_from_trainer
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- financial-sentiment-analysis
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- sentiment-analysis
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- sentence_50agree
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- financial
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- stocks
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- sentiment
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datasets:
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- financial_phrasebank
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- Kaggle Self label
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- nickmuchi/financial-classification
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widget:
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- text: "The USD rallied by 3% last night as the Fed hiked interest rates"
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example_title: "Bullish Sentiment"
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- text: "Covid-19 cases have been increasing over the past few months impacting earnings for global firms"
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example_title: "Bearish Sentiment"
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- text: "the USD has been trending lower"
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example_title: "Mildly Bearish Sentiment"
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- text: "The USD rallied by 3% last night as the Fed hiked interest rates however, higher interest rates will increase mortgage costs for homeowners"
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example_title: "Neutral"
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metrics:
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- accuracy
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- f1
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results: []
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---
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# deberta-v3-base-finetuned-finance-text-classification
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the sentence_50Agree [financial-phrasebank + Kaggle Dataset](https://huggingface.co/datasets/nickmuchi/financial-classification), a dataset consisting of 4840 Financial News categorised by sentiment (negative, neutral, positive). The Kaggle dataset includes Covid-19 sentiment data and can be found here: [sentiment-classification-selflabel-dataset](https://www.kaggle.com/percyzheng/sentiment-classification-selflabel-dataset).
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It achieves the following results on the evaluation set:
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- Loss: 0.7687
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- Accuracy: 0.8913
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