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