tomaarsen
/

span-marker-bert-base-fewnerd-fine-super

@@ -6,6 +6,7 @@ tags:
 - token-classification
 - ner
 - named-entity-recognition
 pipeline_tag: token-classification
 widget:
 - text: "Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris."
@@ -46,19 +47,100 @@ metrics:
 - precision
 ---
-# SpanMarker for Named Entity Recognition
-This is a [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) model that can be used for Named Entity Recognition. In particular, this SpanMarker model uses [bert-base-cased](https://huggingface.co/bert-base-cased) as the underlying encoder.
-## Usage
-To use this model for inference, first install the `span_marker` library:
-```bash
-pip install span_marker
-```
-You can then run inference with this model like so:
 ```python
 from span_marker import SpanMarkerModel
@@ -69,4 +151,60 @@ model = SpanMarkerModel.from_pretrained("tomaarsen/span-marker-bert-base-fewnerd
 entities = model.predict("Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris.")
 ```
-See the [SpanMarker](https://github.com/tomaarsen/SpanMarkerNER) repository for documentation and additional information on this library.

 - token-classification
 - ner
 - named-entity-recognition
+- generated_from_span_marker_trainer
 pipeline_tag: token-classification
 widget:
 - text: "Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris."
 - precision
 ---
+# SpanMarker with bert-base-cased 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 [bert-base-cased](https://huggingface.co/models/bert-base-cased) as the underlying encoder.
+## Model Details
+### Model Description
+- **Model Type:** SpanMarker
+- **Encoder:** [bert-base-cased](https://huggingface.co/models/bert-base-cased)
+- **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                     | "Street Cents", "Corazones", "The Gale Storm Show : Oh , Susanna"                                        |
+| art-film                                 | "Bosch", "L'Atlantide", "Shawshank Redemption"                                                           |
+| art-music                                | "Atkinson , Danko and Ford ( with Brockie and Hilton )", "Champion Lover", "Hollywood Studio Symphony"   |
+| art-other                                | "Aphrodite of Milos", "Venus de Milo", "The Today Show"                                                  |
+| art-painting                             | "Production/Reproduction", "Touit", "Cofiwch Dryweryn"                                                   |
+| art-writtenart                           | "Imelda de ' Lambertazzi", "Time", "The Seven Year Itch"                                                 |
+| building-airport                         | "Luton Airport", "Newark Liberty International Airport", "Sheremetyevo International Airport"            |
+| building-hospital                        | "Hokkaido University Hospital", "Yeungnam University Hospital", "Memorial Sloan-Kettering Cancer Center" |
+| building-hotel                           | "The Standard Hotel", "Radisson Blu Sea Plaza Hotel", "Flamingo Hotel"                                   |
+| building-library                         | "British Library", "Berlin State Library", "Bayerische Staatsbibliothek"                                 |
+| building-other                           | "Communiplex", "Alpha Recording Studios", "Henry Ford Museum"                                            |
+| building-restaurant                      | "Fatburger", "Carnegie Deli", "Trumbull"                                                                 |
+| building-sportsfacility                  | "Glenn Warner Soccer Facility", "Boston Garden", "Sports Center"                                         |
+| building-theater                         | "Pittsburgh Civic Light Opera", "Sanders Theatre", "National Paris Opera"                                |
+| event-attack/battle/war/militaryconflict | "Easter Offensive", "Vietnam War", "Jurist"                                                              |
+| event-disaster                           | "the 1912 North Mount Lyell Disaster", "1693 Sicily earthquake", "1990s North Korean famine"             |
+| event-election                           | "March 1898 elections", "1982 Mitcham and Morden by-election", "Elections to the European Parliament"    |
+| event-other                              | "Eastwood Scoring Stage", "Union for a Popular Movement", "Masaryk Democratic Movement"                  |
+| event-protest                            | "French Revolution", "Russian Revolution", "Iranian Constitutional Revolution"                           |
+| event-sportsevent                        | "National Champions", "World Cup", "Stanley Cup"                                                         |
+| location-GPE                             | "Mediterranean Basin", "the Republic of Croatia", "Croatian"                                             |
+| location-bodiesofwater                   | "Atatürk Dam Lake", "Norfolk coast", "Arthur Kill"                                                       |
+| location-island                          | "Laccadives", "Staten Island", "new Samsat district"                                                     |
+| location-mountain                        | "Salamander Glacier", "Miteirya Ridge", "Ruweisat Ridge"                                                 |
+| location-other                           | "Northern City Line", "Victoria line", "Cartuther"                                                       |
+| location-park                            | "Gramercy Park", "Painted Desert Community Complex Historic District", "Shenandoah National Park"        |
+| location-road/railway/highway/transit    | "Friern Barnet Road", "Newark-Elizabeth Rail Link", "NJT"                                                |
+| organization-company                     | "Dixy Chicken", "Texas Chicken", "Church 's Chicken"                                                     |
+| organization-education                   | "MIT", "Belfast Royal Academy and the Ulster College of Physical Education", "Barnard College"           |
+| organization-government/governmentagency | "Congregazione dei Nobili", "Diet", "Supreme Court"                                                      |
+| organization-media/newspaper             | "TimeOut Melbourne", "Clash", "Al Jazeera"                                                               |
+| organization-other                       | "Defence Sector C", "IAEA", "4th Army"                                                                   |
+| organization-politicalparty              | "Shimpotō", "Al Wafa ' Islamic", "Kenseitō"                                                              |
+| organization-religion                    | "Jewish", "Christian", "UPCUSA"                                                                          |
+| organization-showorganization            | "Lizzy", "Bochumer Symphoniker", "Mr. Mister"                                                            |
+| organization-sportsleague                | "China League One", "First Division", "NHL"                                                              |
+| organization-sportsteam                  | "Tottenham", "Arsenal", "Luc Alphand Aventures"                                                          |
+| other-astronomything                     | "Zodiac", "Algol", "`` Caput Larvae ''"                                                                  |
+| other-award                              | "GCON", "Order of the Republic of Guinea and Nigeria", "Grand Commander of the Order of the Niger"       |
+| other-biologything                       | "N-terminal lipid", "BAR", "Amphiphysin"                                                                 |
+| other-chemicalthing                      | "uranium", "carbon dioxide", "sulfur"                                                                    |
+| other-currency                           | "$", "Travancore Rupee", "lac crore"                                                                     |
+| other-disease                            | "French Dysentery Epidemic of 1779", "hypothyroidism", "bladder cancer"                                  |
+| other-educationaldegree                  | "Master", "Bachelor", "BSc ( Hons ) in physics"                                                          |
+| other-god                                | "El", "Fujin", "Raijin"                                                                                  |
+| other-language                           | "Breton-speaking", "English", "Latin"                                                                    |
+| other-law                                | "Thirty Years ' Peace", "Leahy–Smith America Invents Act ( AIA", "United States Freedom Support Act"     |
+| other-livingthing                        | "insects", "monkeys", "patchouli"                                                                        |
+| other-medical                            | "Pediatrics", "amitriptyline", "pediatrician"                                                            |
+| person-actor                             | "Ellaline Terriss", "Tchéky Karyo", "Edmund Payne"                                                       |
+| person-artist/author                     | "George Axelrod", "Gaetano Donizett", "Hicks"                                                            |
+| person-athlete                           | "Jaguar", "Neville", "Tozawa"                                                                            |
+| person-director                          | "Bob Swaim", "Richard Quine", "Frank Darabont"                                                           |
+| person-other                             | "Richard Benson", "Holden", "Campbell"                                                                   |
+| person-politician                        | "William", "Rivière", "Emeric"                                                                           |
+| person-scholar                           | "Stedman", "Wurdack", "Stalmine"                                                                         |
+| person-soldier                           | "Helmuth Weidling", "Krukenberg", "Joachim Ziegler"                                                      |
+| product-airplane                         | "Luton", "Spey-equipped FGR.2s", "EC135T2 CPDS"                                                          |
+| product-car                              | "100EX", "Corvettes - GT1 C6R", "Phantom"                                                                |
+| product-food                             | "red grape", "yakiniku", "V. labrusca"                                                                   |
+| product-game                             | "Airforce Delta", "Hardcore RPG", "Splinter Cell"                                                        |
+| product-other                            | "Fairbottom Bobs", "X11", "PDP-1"                                                                        |
+| product-ship                             | "Congress", "Essex", "HMS `` Chinkara ''"                                                                |
+| product-software                         | "AmiPDF", "Apdf", "Wikipedia"                                                                            |
+| product-train                            | "High Speed Trains", "55022", "Royal Scots Grey"                                                         |
+| product-weapon                           | "AR-15 's", "ZU-23-2M Wróbel", "ZU-23-2MR Wróbel II"                                                     |
+## Uses
+### Direct Use
 ```python
 from span_marker import SpanMarkerModel
 entities = model.predict("Amelia Earhart flew her single engine Lockheed Vega 5B across the Atlantic to Paris.")
 ```
+### 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("tomaarsen/span-marker-bert-base-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("tomaarsen/span-marker-bert-base-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: 5e-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 Hardware
+- **On Cloud**: No
+- **GPU Model**: 1 x NVIDIA GeForce RTX 3090
+- **CPU Model**: 13th Gen Intel(R) Core(TM) i7-13700K
+- **RAM Size**: 31.78 GB
+### Framework Versions
+- Python: 3.9.16
+- SpanMarker: 1.3.1.dev
+- Transformers : 4.29.2
+- PyTorch: 2.0.1+cu118
+- Datasets: 2.14.3
+- Tokenizers: 0.13.2