Mariia
commited on
Commit
•
3f19ab6
1
Parent(s):
82f8115
Update README.md
Browse files
README.md
CHANGED
|
@@ -26,7 +26,7 @@ This resource derives from the participation of the SINAI team in [Mining Social
|
|
| 26 |
|
| 27 |
Our approach is based on a [model pre-trained on general-domain text](https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne). In order to leverage large scale additional [Silver Standard data](https://zenodo.org/record/6803567/preview/SocialDisNER_LargeScale_additionaldata.zip#tree_item0) with automatically generated labels provided by task’s organisers we designed a two-stage fine-tuning framework. The figure below illustrated the fine-tuning process:
|
| 28 |
|
| 29 |
-
|
| 30 |
|
| 31 |
# Results
|
| 32 |
The model contained in this repository constitutes the fundament of the NER system presented by the SINAI team on SocialDisNER. Enhanced with data [`pysentimiento`](https://github.com/pysentimiento/pysentimiento) pre-processing and rule-based submission post-processing, it obtained encouraging results during the official evaluation, which are summarised in the table below.
|
|
|
|
| 26 |
|
| 27 |
Our approach is based on a [model pre-trained on general-domain text](https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne). In order to leverage large scale additional [Silver Standard data](https://zenodo.org/record/6803567/preview/SocialDisNER_LargeScale_additionaldata.zip#tree_item0) with automatically generated labels provided by task’s organisers we designed a two-stage fine-tuning framework. The figure below illustrated the fine-tuning process:
|
| 28 |
|
| 29 |
+
<img src="https://huggingface.co/chizhikchi/spanish-SM-disease-finder/blob/main/SocialDisNER.png" alt="Two-step fine-tuning" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
|
| 30 |
|
| 31 |
# Results
|
| 32 |
The model contained in this repository constitutes the fundament of the NER system presented by the SINAI team on SocialDisNER. Enhanced with data [`pysentimiento`](https://github.com/pysentimiento/pysentimiento) pre-processing and rule-based submission post-processing, it obtained encouraging results during the official evaluation, which are summarised in the table below.
|