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README.md
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### Dataset
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`roberta_classics_ner` was fine-tuned and evaluated on `EpiBau`, a dataset which has not been released publicly yet. It is composed of four volumes of
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Entity counts of the `Epibau` dataset are the following:
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### Results
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Trained and tested on `EpiBau` with a 85-15 split, the model yields a general F1 score of **.82** (micro-averages). Detailed scores are displayed below. Evaluation was performed with the [CLEF-HIPE-scorer](https://github.com/impresso/CLEF-HIPE-2020-scorer), in strict mode)
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| metric | AAUTHOR | AWORK | REFSCOPE | REFAUWORK |
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### Dataset
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`roberta_classics_ner` was fine-tuned and evaluated on `EpiBau`, a dataset which has not been released publicly yet. It is composed of four volumes of [Structures of Epic Poetry](https://www.epische-bauformen.uni-rostock.de/), a compendium on the narrative patterns and structural elements in ancient epic.
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Entity counts of the `Epibau` dataset are the following:
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### Results
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The model was developed in the context of experiments reported [here](http://infoscience.epfl.ch/record/291236?&ln=en).Trained and tested on `EpiBau` with a 85-15 split, the model yields a general F1 score of **.82** (micro-averages). Detailed scores are displayed below. Evaluation was performed with the [CLEF-HIPE-scorer](https://github.com/impresso/CLEF-HIPE-2020-scorer), in strict mode)
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| metric | AAUTHOR | AWORK | REFSCOPE | REFAUWORK |
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