language: es
datasets:
- squad_es
- hackathon-pln-es/biomed_squad_es_v2
metrics:
- f1
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
--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 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