| --- |
| tags: |
| - named-entity-recognition |
| - clinical-nlp |
| - multiclinner |
| - multi-head-crf |
| - token-classification |
| language: |
| - en |
| license: apache-2.0 |
| --- |
| |
| # MultiClinNER EN Models |
|
|
| Clinical NER models for EN, trained with Multi-Head CRF architecture. |
|
|
| ## Best Model |
|
|
| - **Model**: `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Arandom-%0.25-P0.5-42` |
| - **Best F1**: 0.7368 |
| - **Branch**: `main` |
|
|
| ## Usage |
|
|
| ```python |
| # Load the best model (main branch) |
| from transformers import AutoTokenizer, AutoModelForTokenClassification |
| |
| model = AutoModelForTokenClassification.from_pretrained("IEETA/MultiClinNER-EN") |
| tokenizer = AutoTokenizer.from_pretrained("IEETA/MultiClinNER-EN") |
| |
| # Load a specific model variant |
| model = AutoModelForTokenClassification.from_pretrained("IEETA/MultiClinNER-EN", revision="BRANCH_NAME") |
| ``` |
|
|
| ## All Models (20 variants) |
|
|
| | Branch | Model | Best? | |
| |--------|-------|-------| |
| | `main` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Arandom-%0.25-P0.5-42` | **Yes** | |
| | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Anone-pct0.2-P0.5-123` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Anone-%0.2-P0.5-123` | | |
| | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Anone-pct0.2-P0.5-42` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Anone-%0.2-P0.5-42` | | |
| | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Anone-pct0.2-P0.5-456` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Anone-%0.2-P0.5-456` | | |
| | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Anone-pct0.2-P0.5-999` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Anone-%0.2-P0.5-999` | | |
| | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Arandom-pct0.1-P0.5-123` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Arandom-%0.1-P0.5-123` | | |
| | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Arandom-pct0.1-P0.5-42` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Arandom-%0.1-P0.5-42` | | |
| | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Arandom-pct0.1-P0.5-456` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Arandom-%0.1-P0.5-456` | | |
| | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Arandom-pct0.1-P0.5-999` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Arandom-%0.1-P0.5-999` | | |
| | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Arandom-pct0.25-P0.5-123` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Arandom-%0.25-P0.5-123` | | |
| | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Arandom-pct0.25-P0.5-456` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Arandom-%0.25-P0.5-456` | | |
| | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Arandom-pct0.25-P0.5-999` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Arandom-%0.25-P0.5-999` | | |
| | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Aukn-pct0.25-P0.2-123` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Aukn-%0.25-P0.2-123` | | |
| | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Aukn-pct0.25-P0.2-42` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Aukn-%0.25-P0.2-42` | | |
| | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Aukn-pct0.25-P0.2-456` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Aukn-%0.25-P0.2-456` | | |
| | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Aukn-pct0.25-P0.2-999` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Aukn-%0.25-P0.2-999` | | |
| | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Aukn-pct0.25-P0.5-123` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Aukn-%0.25-P0.5-123` | | |
| | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Aukn-pct0.25-P0.5-42` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Aukn-%0.25-P0.5-42` | | |
| | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Aukn-pct0.25-P0.5-456` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Aukn-%0.25-P0.5-456` | | |
| | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Aukn-pct0.25-P0.5-999` | `microsoft-BiomedNLP-PubMedBERT-large-uncased-abstract-C64-H3-E30-Aukn-%0.25-P0.5-999` | | |
|
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