Token Classification
SpanMarker
PyTorch
Safetensors
English
ner
named-entity-recognition
Eval Results (legacy)
Instructions to use tomaarsen/span-marker-xlm-roberta-large-conll03-doc-context with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- SpanMarker
How to use tomaarsen/span-marker-xlm-roberta-large-conll03-doc-context with SpanMarker:
from span_marker import SpanMarkerModel model = SpanMarkerModel.from_pretrained("tomaarsen/span-marker-xlm-roberta-large-conll03-doc-context") - Notebooks
- Google Colab
- Kaggle
Commit ·
2d88b8f
1
Parent(s): addf7c3
Librarian Bot: Add base_model information to model (#2)
Browse files- Librarian Bot: Add base_model information to model (48e1dc2d4d127e144c0974cedaa1d4c489145077)
Co-authored-by: Librarian Bot (Bot) <librarian-bot@users.noreply.huggingface.co>
README.md
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---
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license: apache-2.0
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library_name: span-marker
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tags:
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- token-classification
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- ner
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- named-entity-recognition
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pipeline_tag: token-classification
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widget:
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model-index:
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datasets:
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- conll2003
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- tomaarsen/conll2003
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language:
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- en
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metrics:
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- precision
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---
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# SpanMarker for Named Entity Recognition
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language:
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- en
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license: apache-2.0
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library_name: span-marker
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tags:
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- token-classification
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- ner
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- named-entity-recognition
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datasets:
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- conll2003
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- tomaarsen/conll2003
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metrics:
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- f1
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- recall
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- precision
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pipeline_tag: token-classification
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widget:
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- text: Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic
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to Paris.
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example_title: Amelia Earhart
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base_model: xlm-roberta-large
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model-index:
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- name: SpanMarker w. xlm-roberta-large on CoNLL03 with document-level context by
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Tom Aarsen
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results:
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- task:
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type: token-classification
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name: Named Entity Recognition
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dataset:
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name: CoNLL03 w. document context
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type: conll2003
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split: test
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revision: 01ad4ad271976c5258b9ed9b910469a806ff3288
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metrics:
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- type: f1
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value: 0.9442
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name: F1
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- type: precision
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value: 0.9411
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name: Precision
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- type: recall
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value: 0.9473
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name: Recall
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---
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# SpanMarker for Named Entity Recognition
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