metadata
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
language:
- en
metrics:
- accuracy
- f1
pipeline_tag: token-classification
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
| Data | Accuracy |
|---|---|
| validation | 0.972 |