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surrey-nlp/flair-abbr-roberta-pubmed-plos-unfiltered

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Model age
2.6y ago
created 2024-03-08
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Metadata

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pytorch license:cc-by-sa-4.0 region:us

Related

Total size
1.74 GB
Files
3
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2024-05-28 08:50

Files by quantization

Auxiliary files 3 files 1.74 GB
pytorch_model.bin 1.74 GB 99fb4ed3 download
.gitattributes 1.48 KB a6344aac download
README.md 898 B e9d0fab7 download

README current version from Hugging Face


license: cc-by-sa-4.0

Flair-abbr-roberta-pubmed-plos-unfiltered

This is a stacked model of embeddings from roberta-large, HunFlair pubmed models and character-level language models trained on PLOS, fine-tuning on the PLODv2 unfiltered dataset.
It is released with our LREC-COLING 2024 publication Using character-level models for efficient abbreviation and long-form detection. It achieves the following results on the test set:

Results on abbreviations:

  • Precision: 0.8977
  • Recall: 0.9351
  • F1: 0.9160

Results on long forms:

  • Precision: 0.8726
  • Recall: 0.9260
  • F1: 0.8985

README history 5 versions

The author's README evolved over time. Click a version to see its content at that point.

  1. 2024-05-28Update README.md858b69a898 B
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  2. 2024-03-21Update README.mdc79fde3784 B
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  3. 2024-03-08Update README.md72e182a716 B
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  4. 2024-03-08Update README.md1a21491715 B
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  5. 2024-03-08initial commit7a556a730 B
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