Token Classification
Transformers
Safetensors
Hebrew
English
bert
named-entity-recognition
hebrew-manuscripts
marc
role-classification
Instructions to use alexgoldberg/hebrew-manuscript-joint-ner-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alexgoldberg/hebrew-manuscript-joint-ner-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="alexgoldberg/hebrew-manuscript-joint-ner-v2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("alexgoldberg/hebrew-manuscript-joint-ner-v2") model = AutoModelForTokenClassification.from_pretrained("alexgoldberg/hebrew-manuscript-joint-ner-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,777 Bytes
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"n_items": 904,
"strict_span_role": {
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"recall": 0.817989417989418,
"f1": 0.8031168831168832,
"tp": 773,
"fp": 207,
"fn": 172
},
"normalised_span_role": {
"precision": 0.7887755102040817,
"recall": 0.817989417989418,
"f1": 0.8031168831168832,
"tp": 773,
"fp": 207,
"fn": 172
},
"normalised_name_only": {
"precision": 0.8510204081632653,
"recall": 0.8825396825396825,
"f1": 0.8664935064935065,
"tp": 834,
"fp": 146,
"fn": 111
},
"role_given_name": {
"matched_names": 834,
"correct_roles": 773,
"accuracy": 0.9268585131894485
},
"per_role_normalised_span_role": {
"AUTHOR": {
"precision": 0.8827586206896552,
"recall": 0.8533333333333334,
"f1": 0.8677966101694914,
"tp": 128,
"fp": 17,
"fn": 22
},
"CENSOR": {
"precision": 0.8736842105263158,
"recall": 0.8924731182795699,
"f1": 0.8829787234042553,
"tp": 83,
"fp": 12,
"fn": 10
},
"COMMENTATOR": {
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"tp": 7,
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},
"OWNER": {
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"recall": 0.7700348432055749,
"f1": 0.7330016583747927,
"tp": 221,
"fp": 95,
"fn": 66
},
"TRANSCRIBER": {
"precision": 0.8033240997229917,
"recall": 0.8192090395480226,
"f1": 0.8111888111888111,
"tp": 290,
"fp": 71,
"fn": 64
},
"TRANSLATOR": {
"precision": 0.8627450980392157,
"recall": 0.9565217391304348,
"f1": 0.9072164948453608,
"tp": 44,
"fp": 7,
"fn": 2
}
}
} |