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en_medextract_lg
ken-dwyer/en_medextract_lg
en_medextract_lg is a token classification model from ken-dwyer. Use it when you need labels on individual words, such as names. It is set up for spacy.
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1.2 GB
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Other643 MB · 52%
At a glance
- Task
- Token Classification
- Library
- spacy
- Access
- Public
- Created
- Jan 11, 2024
- Updated
- Jan 11, 2024
- SHA
- f4042599
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Model card
From the Hugging Face model README
| Feature | Description |
|---|---|
| Name | en_medextract_lg |
| Version | 0.0.0 |
| spaCy | >=3.7.2,<3.8.0 |
| Default Pipeline | tok2vec, ner |
| Components | tok2vec, ner |
| Vectors | 514157 keys, 514157 unique vectors (300 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
<details> <summary>View label scheme (9 labels for 1 components)</summary>| Component | Labels |
|---|---|
ner | ADE, Dosage, Drug, Duration, Form, Frequency, Reason, Route, Strength |
Accuracy
| Type | Score |
|---|---|
ENTS_F | 85.39 |
ENTS_P | 88.01 |
ENTS_R | 82.93 |
TOK2VEC_LOSS | 15451506.09 |
NER_LOSS | 1885361.05 |
- Task
- Token Classification
- Library
- spacy
- Languages
- en
- Created
- Jan 11, 2024
- Updated
- Jan 11, 2024