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README.md
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#### Limitations and bias
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Note that this model had the best performance for drug and disease entities. However BioBERT was able to recognize better the other intervention types.
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This model is limited by its training dataset of entity-annotated clinical trial registry records from a specific span of time and focused on the field of neuroscience. This may not generalize well for all use cases in different domains. Furthermore, the model occassionally tags subword tokens as entities and post-processing of results may be necessary to handle those cases.
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## Training data
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This model was fine-tuned on [NeuroTrialNER](https://huggingface.co/datasets/bigbio/neurotrial_ner) dataset.
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#### Limitations and bias
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This model is limited by its training dataset of entity-annotated clinical trial registry records from a specific span of time and focused on the field of neuroscience. This may not generalize well for all use cases in different domains. Furthermore, the model occassionally tags subword tokens as entities and post-processing of results may be necessary to handle those cases.
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⚠️ This model had the best performance for drug and disease entities. However BioBERT was able to recognize better the other intervention types.
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## Training data
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This model was fine-tuned on [NeuroTrialNER](https://huggingface.co/datasets/bigbio/neurotrial_ner) dataset.
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