
# biomedtra-small for QA 

This model was trained as part of the "Extractive QA Biomedicine" project developed during the 2022 [Hackathon](https://somosnlp.org/hackathon) organized by SOMOS NLP.

## Motivation

Recent research has made available Spanish Language Models trained on Biomedical corpus. This project explores the use of these new models to generate extractive Question Answering models for Biomedicine, and compares their effectiveness with general masked language models.

The models trained during the [Hackathon](https://somosnlp.org/hackathon) were:

[hackathon-pln-es/roberta-base-bne-squad2-es](https://huggingface.co/hackathon-pln-es/roberta-base-bne-squad2-es)

[hackathon-pln-es/roberta-base-biomedical-clinical-es-squad2-es](https://huggingface.co/hackathon-pln-es/roberta-base-biomedical-clinical-es-squad2-es)

[hackathon-pln-es/roberta-base-biomedical-es-squad2-es](https://huggingface.co/hackathon-pln-es/roberta-base-biomedical-es-squad2-es)

[hackathon-pln-es/biomedtra-small-es-squad2-es](https://huggingface.co/hackathon-pln-es/biomedtra-small-es-squad2-es)

## Description

This model is a fine-tuned version of [mrm8488/biomedtra-small-es](https://huggingface.co/mrm8488/biomedtra-small-es) on the [squad_es (v2)](https://huggingface.co/datasets/squad_es) training dataset.


## Hyperparameters

The hyperparameters were chosen based on those used in [deepset/electra-base-squad2](https://huggingface.co/deepset/electra-base-squad2), an english-based model trained for similar purposes

```
  --num_train_epochs 10 \
  --learning_rate 1e-4 \
  --max_seq_length 384 \
  --doc_stride 128 \

```

## Performance

Evaluated on the [hackathon-pln-es/biomed_squad_es_v2](https://huggingface.co/datasets/hackathon-pln-es/biomed_squad_es_v2) dev set.

|Model                                                         |Base Model Domain|exact  |f1     |HasAns_exact|HasAns_f1|NoAns_exact|NoAns_f1|
|--------------------------------------------------------------|-----------------|-------|-------|------------|---------|-----------|--------|
|hackathon-pln-es/roberta-base-bne-squad2-es                   |General          |67.6341|75.6988|53.7367     |70.0526  |81.2174    |81.2174 |
|hackathon-pln-es/roberta-base-biomedical-clinical-es-squad2-es|Biomedical       |66.8426|75.2346|53.0249     |70.0031  |80.3478    |80.3478 |
|hackathon-pln-es/roberta-base-biomedical-es-squad2-es         |Biomedical       |67.6341|74.5612|47.6868     |61.7012  |87.1304    | 87.1304|
|hackathon-pln-es/biomedtra-small-es-squad2-es                 |Biomedical       |34.4767|44.3294|45.3737     |65.307   |23.8261    |23.8261 |

## Team
Santiago Maximo: [smaximo](https://huggingface.co/smaximo)
{"language": "es", "datasets": ["squad_es", "hackathon-pln-es/biomed_squad_es_v2"], "metrics": ["f1"]}
transformers pytorch electra question-answering es dataset:squad_es dataset:hackathon-pln-es/biomed_squad_es_v2 endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #electra #question-answering #es #dataset-squad_es #dataset-hackathon-pln-es/biomed_squad_es_v2 #endpoints_compatible #has_space #region-us 

biomedtra-small for QA
======================


This model was trained as part of the "Extractive QA Biomedicine" project developed during the 2022 Hackathon organized by SOMOS NLP.


Motivation
----------


Recent research has made available Spanish Language Models trained on Biomedical corpus. This project explores the use of these new models to generate extractive Question Answering models for Biomedicine, and compares their effectiveness with general masked language models.


The models trained during the Hackathon were:


hackathon-pln-es/roberta-base-bne-squad2-es


hackathon-pln-es/roberta-base-biomedical-clinical-es-squad2-es


hackathon-pln-es/roberta-base-biomedical-es-squad2-es


hackathon-pln-es/biomedtra-small-es-squad2-es


Description
-----------


This model is a fine-tuned version of mrm8488/biomedtra-small-es on the squad\_es (v2) training dataset.


Hyperparameters
---------------


The hyperparameters were chosen based on those used in deepset/electra-base-squad2, an english-based model trained for similar purposes


Performance
-----------


Evaluated on the hackathon-pln-es/biomed\_squad\_es\_v2 dev set.



Team
----


Santiago Maximo: smaximo



TAGS
#transformers #pytorch #electra #question-answering #es #dataset-squad_es #dataset-hackathon-pln-es/biomed_squad_es_v2 #endpoints_compatible #has_space #region-us 

passage: TAGS
#transformers #pytorch #electra #question-answering #es #dataset-squad_es #dataset-hackathon-pln-es/biomed_squad_es_v2 #endpoints_compatible #has_space #region-us 
