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--- |
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tags: |
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- finance |
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- finbert |
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- market |
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- financial |
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- generated_from_trainer |
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- financial |
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- stocks |
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- sentiment |
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- text-classification |
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widget: |
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- text: "Asian Stocks Set to Decline Amidst Growth Worries" |
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output: |
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- label: POSITIVE |
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score: 0.14 |
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- label: INDECISIVE |
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score: 0.25 |
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- label: NEGATIVE |
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score: 0.61 |
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- text: "High inflation expectations becoming part of the American consumers behavioral norm" |
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output: |
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- label: POSITIVE |
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score: 0.49 |
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- label: INDECISIVE |
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score: 0.30 |
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- label: NEGATIVE |
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score: 0.21 |
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datasets: |
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- FinBERT_market_based/autotrain-data |
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--- |
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# Model Card for Finetuned FinBERT on Market-Based Facts |
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Our FinBERT model, finetuned on impactful news headlines about global equity markets, has shown significant performance improvements over standard models. |
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Its training on real-world market impact rather than subjective financial expert opinions sets a new standard for unbiased financial sentiment analysis. π |
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**Outperforms FinBERT** |
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- π― +25% precision |
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- π +18% recall |
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**Outperforms DistilRoBERTa finetuned for finance** |
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- π― +22% precision |
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- π +15% recall |
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**Outperforms GPT-4 zero-shot learning** |
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- π― +15% precision |
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- π +8.2% recall |
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## Validation Metrics |
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| Metric | Value | |
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|--------------------|-----------------------| |
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| loss | 0.9176467061042786 | |
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| f1_macro | 0.49749240436690023 | |
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| f1_micro | 0.5627105467737756 | |
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| f1_weighted | 0.5279720746084178 | |
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| precision_macro | 0.5386355574899088 | |
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| precision_micro | 0.5627105467737756 | |
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| precision_weighted | 0.5462149036191247 | |
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| recall_macro | 0.517542664344306 | |
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| recall_micro | 0.5627105467737756 | |
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| recall_weighted | 0.5627105467737756 | |
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| accuracy | 0.5627105467737756 | |
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This model has been developed after publishing in the Risk Forum 2024 conference a paper that can be found here (https://arxiv.org/abs/2401.05447). |
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