Add widget examples + link to uncased model
#2
by
tomaarsen
HF staff
- opened
README.md
CHANGED
@@ -33,6 +33,51 @@ metrics:
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- recall
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- f1
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pipeline_tag: token-classification
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language:
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- de
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- en
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@@ -52,7 +97,11 @@ should probably proofread and complete it, then remove this comment. -->
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# span-marker-bert-base-multilingual-cased-multinerd
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an [Babelscape/multinerd](https://huggingface.co/datasets/Babelscape/multinerd) dataset.
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- Loss: 0.0049
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- Overall Precision: 0.9242
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- Overall Recall: 0.9281
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- recall
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- f1
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pipeline_tag: token-classification
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widget:
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- text: "Amelia Earthart flog mit ihrer einmotorigen Lockheed Vega 5B über den Atlantik nach Paris."
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example_title: "German"
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- text: "Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris."
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example_title: "English"
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- text: "Amelia Earthart voló su Lockheed Vega 5B monomotor a través del Océano Atlántico hasta París."
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example_title: "Spanish"
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- text: "Amelia Earthart a fait voler son monomoteur Lockheed Vega 5B à travers l'ocean Atlantique jusqu'à Paris."
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example_title: "French"
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- text: "Amelia Earhart ha volato con il suo monomotore Lockheed Vega 5B attraverso l'Atlantico fino a Parigi."
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example_title: "Italian"
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- text: "Amelia Earthart vloog met haar één-motorige Lockheed Vega 5B over de Atlantische Oceaan naar Parijs."
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example_title: "Dutch"
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- text: "Amelia Earthart przeleciała swoim jednosilnikowym samolotem Lockheed Vega 5B przez Ocean Atlantycki do Paryża."
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example_title: "Polish"
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- text: "Amelia Earhart voou em seu monomotor Lockheed Vega 5B através do Atlântico para Paris."
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example_title: "Portuguese"
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- text: "Амелия Эртхарт перелетела на своем одномоторном самолете Lockheed Vega 5B через Атлантический океан в Париж."
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example_title: "Russian"
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- text: "Amelia Earthart flaug eins hreyfils Lockheed Vega 5B yfir Atlantshafið til Parísar."
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example_title: "Icelandic"
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- text: "Η Amelia Earthart πέταξε το μονοκινητήριο Lockheed Vega 5B της πέρα από τον Ατλαντικό Ωκεανό στο Παρίσι."
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example_title: "Greek"
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- text: "Amelia Earhartová přeletěla se svým jednomotorovým Lockheed Vega 5B přes Atlantik do Paříže."
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example_title: "Czech"
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- text: "Amelia Earhart lensi yksimoottorisella Lockheed Vega 5B:llä Atlantin yli Pariisiin."
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example_title: "Finnish"
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- text: "Amelia Earhart fløj med sin enmotoriske Lockheed Vega 5B over Atlanten til Paris."
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example_title: "Danish"
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- text: "Amelia Earhart flög sin enmotoriga Lockheed Vega 5B över Atlanten till Paris."
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example_title: "Swedish"
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- text: "Amelia Earhart fløy sin enmotoriske Lockheed Vega 5B over Atlanterhavet til Paris."
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example_title: "Norwegian"
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- text: "Amelia Earhart și-a zburat cu un singur motor Lockheed Vega 5B peste Atlantic până la Paris."
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example_title: "Romanian"
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- text: "Amelia Earhart menerbangkan mesin tunggal Lockheed Vega 5B melintasi Atlantik ke Paris."
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example_title: "Indonesian"
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- text: "Амелія Эрхарт пераляцела на сваім аднаматорным Lockheed Vega 5B праз Атлантыку ў Парыж."
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example_title: "Belarusian"
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- text: "Амелія Ергарт перелетіла на своєму одномоторному літаку Lockheed Vega 5B через Атлантику до Парижа."
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example_title: "Ukrainian"
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- text: "Amelia Earhart preletjela je svojim jednomotornim zrakoplovom Lockheed Vega 5B preko Atlantika do Pariza."
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example_title: "Croatian"
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- text: "Amelia Earhart lendas oma ühemootoriga Lockheed Vega 5B üle Atlandi ookeani Pariisi ."
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example_title: "Estonian"
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language:
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- de
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- en
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# span-marker-bert-base-multilingual-cased-multinerd
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an [Babelscape/multinerd](https://huggingface.co/datasets/Babelscape/multinerd) dataset.
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Is your data not (always) capitalized correctly? Then consider using the uncased variant of this model instead for better performance:
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[lxyuan/span-marker-bert-base-multilingual-uncased-multinerd](https://huggingface.co/lxyuan/span-marker-bert-base-multilingual-uncased-multinerd).
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This model achieves the following results on the evaluation set:
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- Loss: 0.0049
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- Overall Precision: 0.9242
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- Overall Recall: 0.9281
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