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README.md
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The model is trained with the hyperparameters used by [Nițoi et al. (2023)](https://www.sciencedirect.com/science/article/abs/pii/S2214635023000230).
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In addition, different hyperparameters, seeds, and reinitialization of the first L layers were tested. The performance seems relatively stable across hyperparameter settings.
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Alongside these models, FinBERT, different versions of RoBERTa, and EconBERT were tested. The performance of the BERT-based models reported here is significantly better.
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## Results
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| [CBSI-bert-base-uncased](https://huggingface.co/brjoey/CBSI-bert-base-uncased) | 0.88 | 0.88 | 0.49 |
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| [CBSI-bert-large-uncased](https://huggingface.co/brjoey/CBSI-bert-large-uncased) | 0.92 | 0.92 | 0.45 |
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## How to use
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The model is trained with the hyperparameters used by [Nițoi et al. (2023)](https://www.sciencedirect.com/science/article/abs/pii/S2214635023000230).
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In addition, different hyperparameters, seeds, and reinitialization of the first L layers were tested. The performance seems relatively stable across hyperparameter settings.
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Alongside these models, FinBERT, different versions of RoBERTa, and EconBERT were tested. The performance of the BERT-based models reported here is significantly better. In addition, fine-tuned ModernBERT versions are also available.
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## Results
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|------------------------------------------------------------------------|----------|----------|------|
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| [CBSI-bert-base-uncased](https://huggingface.co/brjoey/CBSI-bert-base-uncased) | 0.88 | 0.88 | 0.49 |
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| [CBSI-bert-large-uncased](https://huggingface.co/brjoey/CBSI-bert-large-uncased) | 0.92 | 0.92 | 0.45 |
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| [CBSI-ModernBERT-base](https://huggingface.co/your-hf-org/CBSI-ModernBERT-base) | 0.93 | 0.93 | 0.40 |
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| [CBSI-ModernBERT-large](https://huggingface.co/your-hf-org/CBSI-ModernBERT-large) | 0.91 | 0.91 | 0.53 |
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## How to use
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