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---
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](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 | |