# RoBERTa Span Detection 
This model is a fine-tuned model of [roberta-large](https://huggingface.co/roberta-large) after being trained on a **mixture of NER datasets**.

Basically, this model can detect NER spans (with <u>no differenciation on classes</u>). Labels use the IBO format and are: 
- 'B-TAG': beginning token of span
- 'I-TAG': inside token of span
- 'O': token not a span

# Usage
This model has been trained in an efficient way and thus cannot be load directly from HuggingFace's hub. To use that model, please follow instructions on this [repo](https://github.com/AntoineBlanot/efficient-llm).

# Data used for training
- tner/bc5cdr
- tner/bionlp2004
- tner/btc
- tner/conll2003
- tner/fin
- tner/mit_movie_trivia
- tner/mit_restaurant
- tner/multinerd
- tner/ontonotes5
- tner/tweebank_ner
- tner/tweetner7
- tner/wikineural
- tner/wnut2017

# Evaluation results

| Data | Accuracy |
|:---:|:---------:|
| validation | 0.972 |
{"language": ["en"], "datasets": ["tner/bc5cdr", "tner/bionlp2004", "tner/btc", "tner/conll2003", "tner/fin", "tner/mit_movie_trivia", "tner/mit_restaurant", "tner/multinerd", "tner/ontonotes5", "tner/tweebank_ner", "tner/tweetner7", "tner/wikineural", "tner/wnut2017"], "metrics": ["accuracy", "f1"], "pipeline_tag": "token-classification"}
transformers pytorch roberta feature-extraction token-classification en dataset:tner/bc5cdr dataset:tner/bionlp2004 dataset:tner/btc dataset:tner/conll2003 dataset:tner/fin dataset:tner/mit_movie_trivia dataset:tner/mit_restaurant dataset:tner/multinerd dataset:tner/ontonotes5 dataset:tner/tweebank_ner dataset:tner/tweetner7 dataset:tner/wikineural dataset:tner/wnut2017 endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #feature-extraction #token-classification #en #dataset-tner/bc5cdr #dataset-tner/bionlp2004 #dataset-tner/btc #dataset-tner/conll2003 #dataset-tner/fin #dataset-tner/mit_movie_trivia #dataset-tner/mit_restaurant #dataset-tner/multinerd #dataset-tner/ontonotes5 #dataset-tner/tweebank_ner #dataset-tner/tweetner7 #dataset-tner/wikineural #dataset-tner/wnut2017 #endpoints_compatible #region-us 

RoBERTa Span Detection
======================


This model is a fine-tuned model of roberta-large after being trained on a mixture of NER datasets.


Basically, this model can detect NER spans (with no differenciation on classes). Labels use the IBO format and are:


* 'B-TAG': beginning token of span
* 'I-TAG': inside token of span
* 'O': token not a span


Usage
=====


This model has been trained in an efficient way and thus cannot be load directly from HuggingFace's hub. To use that model, please follow instructions on this repo.


Data used for training
======================


* tner/bc5cdr
* tner/bionlp2004
* tner/btc
* tner/conll2003
* tner/fin
* tner/mit\_movie\_trivia
* tner/mit\_restaurant
* tner/multinerd
* tner/ontonotes5
* tner/tweebank\_ner
* tner/tweetner7
* tner/wikineural
* tner/wnut2017


Evaluation results
==================




TAGS
#transformers #pytorch #roberta #feature-extraction #token-classification #en #dataset-tner/bc5cdr #dataset-tner/bionlp2004 #dataset-tner/btc #dataset-tner/conll2003 #dataset-tner/fin #dataset-tner/mit_movie_trivia #dataset-tner/mit_restaurant #dataset-tner/multinerd #dataset-tner/ontonotes5 #dataset-tner/tweebank_ner #dataset-tner/tweetner7 #dataset-tner/wikineural #dataset-tner/wnut2017 #endpoints_compatible #region-us 
