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--- |
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language: |
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- en |
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license: cc-by-sa-4.0 |
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library_name: span-marker |
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tags: |
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- span-marker |
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- token-classification |
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- ner |
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- named-entity-recognition |
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- generated_from_span_marker_trainer |
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datasets: |
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- DFKI-SLT/few-nerd |
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metrics: |
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- precision |
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- recall |
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- f1 |
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widget: |
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- text: The WPC led the international peace movement in the decade after the Second |
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World War, but its failure to speak out against the Soviet suppression of the |
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1956 Hungarian uprising and the resumption of Soviet nuclear tests in 1961 marginalised |
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it, and in the 1960s it was eclipsed by the newer, non-aligned peace organizations |
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like the Campaign for Nuclear Disarmament. |
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- text: Most of the Steven Seagal movie "Under Siege "(co-starring Tommy Lee Jones) |
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was filmed on the, which is docked on Mobile Bay at Battleship Memorial Park and |
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open to the public. |
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- text: 'The Central African CFA franc (French: "franc CFA "or simply "franc ", ISO |
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4217 code: XAF) is the currency of six independent states in Central Africa: Cameroon, |
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Central African Republic, Chad, Republic of the Congo, Equatorial Guinea and Gabon.' |
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- text: Brenner conducted post-doctoral research at Brandeis University with Gregory |
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Petsko and then took his first academic position at Thomas Jefferson University |
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in 1996, moving to Dartmouth Medical School in 2003, where he served as Associate |
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Director for Basic Sciences at Norris Cotton Cancer Center. |
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- text: On Friday, October 27, 2017, the Senate of Spain (Senado) voted 214 to 47 |
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to invoke Article 155 of the Spanish Constitution over Catalonia after the Catalan |
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Parliament declared the independence. |
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pipeline_tag: token-classification |
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base_model: BAAI/bge-base-en-v1.5 |
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model-index: |
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- name: SpanMarker with BAAI/bge-base-en-v1.5 on FewNERD |
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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: FewNERD |
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type: DFKI-SLT/few-nerd |
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split: eval |
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metrics: |
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- type: f1 |
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value: 0.6726393599802055 |
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name: F1 |
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- type: precision |
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value: 0.6740082644628099 |
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name: Precision |
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- type: recall |
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value: 0.6712760046916476 |
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name: Recall |
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--- |
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# SpanMarker with BAAI/bge-base-en-v1.5 on FewNERD |
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This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model trained on the [FewNERD](https://huggingface.co./datasets/DFKI-SLT/few-nerd) dataset that can be used for Named Entity Recognition. This SpanMarker model uses [BAAI/bge-base-en-v1.5](https://huggingface.co./BAAI/bge-base-en-v1.5) as the underlying encoder. |
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## Model Details |
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### Model Description |
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- **Model Type:** SpanMarker |
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- **Encoder:** [BAAI/bge-base-en-v1.5](https://huggingface.co./BAAI/bge-base-en-v1.5) |
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- **Maximum Sequence Length:** 256 tokens |
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- **Maximum Entity Length:** 8 words |
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- **Training Dataset:** [FewNERD](https://huggingface.co./datasets/DFKI-SLT/few-nerd) |
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- **Language:** en |
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- **License:** cc-by-sa-4.0 |
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### Model Sources |
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- **Repository:** [SpanMarker on GitHub](https://github.com/tomaarsen/SpanMarkerNER) |
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- **Thesis:** [SpanMarker For Named Entity Recognition](https://raw.githubusercontent.com/tomaarsen/SpanMarkerNER/main/thesis.pdf) |
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### Model Labels |
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| Label | Examples | |
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|:-----------------------------------------|:---------------------------------------------------------------------------------------------------------| |
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| art-broadcastprogram | "Corazones", "The Gale Storm Show : Oh , Susanna", "Street Cents" | |
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| art-film | "L'Atlantide", "Bosch", "Shawshank Redemption" | |
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| art-music | "Atkinson , Danko and Ford ( with Brockie and Hilton )", "Hollywood Studio Symphony", "Champion Lover" | |
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| art-other | "Venus de Milo", "The Today Show", "Aphrodite of Milos" | |
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| art-painting | "Cofiwch Dryweryn", "Touit", "Production/Reproduction" | |
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| art-writtenart | "Time", "The Seven Year Itch", "Imelda de ' Lambertazzi" | |
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| building-airport | "Newark Liberty International Airport", "Luton Airport", "Sheremetyevo International Airport" | |
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| building-hospital | "Hokkaido University Hospital", "Memorial Sloan-Kettering Cancer Center", "Yeungnam University Hospital" | |
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| building-hotel | "Radisson Blu Sea Plaza Hotel", "Flamingo Hotel", "The Standard Hotel" | |
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| building-library | "Bayerische Staatsbibliothek", "British Library", "Berlin State Library" | |
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| building-other | "Communiplex", "Alpha Recording Studios", "Henry Ford Museum" | |
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| building-restaurant | "Carnegie Deli", "Fatburger", "Trumbull" | |
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| building-sportsfacility | "Boston Garden", "Glenn Warner Soccer Facility", "Sports Center" | |
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| building-theater | "Pittsburgh Civic Light Opera", "National Paris Opera", "Sanders Theatre" | |
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| event-attack/battle/war/militaryconflict | "Jurist", "Vietnam War", "Easter Offensive" | |
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| event-disaster | "1693 Sicily earthquake", "the 1912 North Mount Lyell Disaster", "1990s North Korean famine" | |
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| event-election | "Elections to the European Parliament", "March 1898 elections", "1982 Mitcham and Morden by-election" | |
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| event-other | "Eastwood Scoring Stage", "Masaryk Democratic Movement", "Union for a Popular Movement" | |
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| event-protest | "French Revolution", "Iranian Constitutional Revolution", "Russian Revolution" | |
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| event-sportsevent | "Stanley Cup", "National Champions", "World Cup" | |
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| location-GPE | "Croatian", "the Republic of Croatia", "Mediterranean Basin" | |
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| location-bodiesofwater | "Norfolk coast", "Atatürk Dam Lake", "Arthur Kill" | |
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| location-island | "Staten Island", "Laccadives", "new Samsat district" | |
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| location-mountain | "Ruweisat Ridge", "Salamander Glacier", "Miteirya Ridge" | |
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| location-other | "Victoria line", "Northern City Line", "Cartuther" | |
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| location-park | "Shenandoah National Park", "Gramercy Park", "Painted Desert Community Complex Historic District" | |
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| location-road/railway/highway/transit | "NJT", "Friern Barnet Road", "Newark-Elizabeth Rail Link" | |
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| organization-company | "Texas Chicken", "Dixy Chicken", "Church 's Chicken" | |
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| organization-education | "Barnard College", "MIT", "Belfast Royal Academy and the Ulster College of Physical Education" | |
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| organization-government/governmentagency | "Diet", "Congregazione dei Nobili", "Supreme Court" | |
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| organization-media/newspaper | "Clash", "TimeOut Melbourne", "Al Jazeera" | |
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| organization-other | "Defence Sector C", "IAEA", "4th Army" | |
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| organization-politicalparty | "Al Wafa ' Islamic", "Kenseitō", "Shimpotō" | |
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| organization-religion | "Christian", "Jewish", "UPCUSA" | |
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| organization-showorganization | "Lizzy", "Mr. Mister", "Bochumer Symphoniker" | |
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| organization-sportsleague | "First Division", "China League One", "NHL" | |
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| organization-sportsteam | "Arsenal", "Tottenham", "Luc Alphand Aventures" | |
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| other-astronomything | "Algol", "`` Caput Larvae ''", "Zodiac" | |
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| other-award | "Grand Commander of the Order of the Niger", "Order of the Republic of Guinea and Nigeria", "GCON" | |
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| other-biologything | "BAR", "N-terminal lipid", "Amphiphysin" | |
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| other-chemicalthing | "uranium", "carbon dioxide", "sulfur" | |
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| other-currency | "lac crore", "$", "Travancore Rupee" | |
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| other-disease | "French Dysentery Epidemic of 1779", "hypothyroidism", "bladder cancer" | |
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| other-educationaldegree | "Bachelor", "Master", "BSc ( Hons ) in physics" | |
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| other-god | "El", "Fujin", "Raijin" | |
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| other-language | "English", "Latin", "Breton-speaking" | |
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| other-law | "Thirty Years ' Peace", "Leahy–Smith America Invents Act ( AIA", "United States Freedom Support Act" | |
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| other-livingthing | "monkeys", "insects", "patchouli" | |
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| other-medical | "amitriptyline", "Pediatrics", "pediatrician" | |
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| person-actor | "Ellaline Terriss", "Edmund Payne", "Tchéky Karyo" | |
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| person-artist/author | "Hicks", "George Axelrod", "Gaetano Donizett" | |
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| person-athlete | "Jaguar", "Tozawa", "Neville" | |
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| person-director | "Bob Swaim", "Richard Quine", "Frank Darabont" | |
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| person-other | "Richard Benson", "Holden", "Campbell" | |
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| person-politician | "Emeric", "William", "Rivière" | |
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| person-scholar | "Stalmine", "Wurdack", "Stedman" | |
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| person-soldier | "Krukenberg", "Joachim Ziegler", "Helmuth Weidling" | |
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| product-airplane | "EC135T2 CPDS", "Spey-equipped FGR.2s", "Luton" | |
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| product-car | "100EX", "Phantom", "Corvettes - GT1 C6R" | |
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| product-food | "red grape", "V. labrusca", "yakiniku" | |
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| product-game | "Splinter Cell", "Hardcore RPG", "Airforce Delta" | |
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| product-other | "X11", "PDP-1", "Fairbottom Bobs" | |
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| product-ship | "HMS `` Chinkara ''", "Essex", "Congress" | |
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| product-software | "Wikipedia", "AmiPDF", "Apdf" | |
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| product-train | "55022", "Royal Scots Grey", "High Speed Trains" | |
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| product-weapon | "ZU-23-2M Wróbel", "ZU-23-2MR Wróbel II", "AR-15 's" | |
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## Uses |
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### Direct Use for Inference |
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```python |
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from span_marker import SpanMarkerModel |
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# Download from the 🤗 Hub |
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model = SpanMarkerModel.from_pretrained("guishe/span-marker-bge-base-en-v1.5-fewnerd-fine-super") |
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# Run inference |
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entities = model.predict("Most of the Steven Seagal movie \"Under Siege \"(co-starring Tommy Lee Jones) was filmed on the, which is docked on Mobile Bay at Battleship Memorial Park and open to the public.") |
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``` |
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### Downstream Use |
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You can finetune this model on your own dataset. |
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<details><summary>Click to expand</summary> |
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```python |
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from span_marker import SpanMarkerModel, Trainer |
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# Download from the 🤗 Hub |
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model = SpanMarkerModel.from_pretrained("guishe/span-marker-bge-base-en-v1.5-fewnerd-fine-super") |
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# Specify a Dataset with "tokens" and "ner_tag" columns |
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dataset = load_dataset("conll2003") # For example CoNLL2003 |
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# Initialize a Trainer using the pretrained model & dataset |
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trainer = Trainer( |
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model=model, |
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train_dataset=dataset["train"], |
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eval_dataset=dataset["validation"], |
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) |
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trainer.train() |
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trainer.save_model("guishe/span-marker-bge-base-en-v1.5-fewnerd-fine-super-finetuned") |
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``` |
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</details> |
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## Training Details |
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### Training Set Metrics |
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| Training set | Min | Median | Max | |
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|:----------------------|:----|:--------|:----| |
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| Sentence length | 1 | 24.4945 | 267 | |
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| Entities per sentence | 0 | 2.5832 | 88 | |
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### Training Hyperparameters |
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- learning_rate: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3 |
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### Training Results |
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| Epoch | Step | Validation Loss | Validation Precision | Validation Recall | Validation F1 | Validation Accuracy | |
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|:------:|:-----:|:---------------:|:--------------------:|:-----------------:|:-------------:|:-------------------:| |
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| 0.5964 | 3000 | 0.0324 | 0.6263 | 0.5826 | 0.6037 | 0.8981 | |
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| 1.1928 | 6000 | 0.0278 | 0.6620 | 0.6499 | 0.6559 | 0.9132 | |
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| 1.7893 | 9000 | 0.0264 | 0.6719 | 0.6614 | 0.6666 | 0.9159 | |
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| 2.3857 | 12000 | 0.0260 | 0.6724 | 0.6703 | 0.6714 | 0.9174 | |
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| 2.9821 | 15000 | 0.0258 | 0.6740 | 0.6713 | 0.6726 | 0.9177 | |
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### Framework Versions |
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- Python: 3.10.8 |
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- SpanMarker: 1.4.0 |
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- Transformers: 4.28.0 |
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- PyTorch: 1.13.1+cu117 |
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- Datasets: 2.14.4 |
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- Tokenizers: 0.13.3 |
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## Citation |
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### BibTeX |
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``` |
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@software{Aarsen_SpanMarker, |
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author = {Aarsen, Tom}, |
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license = {Apache-2.0}, |
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title = {{SpanMarker for Named Entity Recognition}}, |
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url = {https://github.com/tomaarsen/SpanMarkerNER} |
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} |
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``` |
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