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README.md
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@@ -22,6 +22,8 @@ The model was trained in a multilabel-sense, using a binary cross-entropy loss p
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(that is **O**utside the span, **B**eginning of the span, **I**nside the span)
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We replaced the standard 768-weight linear layer by 3x768 dense layers with 10\% dropout and ReLu activations.
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Token classification scores (answering the question: ***given** the span, to which class does it belong?*):
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```json
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(that is **O**utside the span, **B**eginning of the span, **I**nside the span)
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We replaced the standard 768-weight linear layer by 3x768 dense layers with 10\% dropout and ReLu activations.
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The weights are a result of chained SLERP over five cross-validated folds.
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Token classification scores (answering the question: ***given** the span, to which class does it belong?*):
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```json
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