|
--- |
|
license: mit |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: biomedical_question_answering |
|
results: [] |
|
datasets: |
|
- Shushant/BiomedicalQuestionAnsweringDataset |
|
language: |
|
- en |
|
metrics: |
|
- exact_match |
|
- f1 |
|
library_name: transformers |
|
pipeline_tag: question-answering |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# biomedical_question_answering |
|
|
|
This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on a custom dataset of question answer pairs annotated from research papers from Pubmed. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.6629 |
|
|
|
## Model description |
|
|
|
Model finetuned on PubmedBERT using custom daatset |
|
|
|
## Intended uses & limitations |
|
|
|
For question answering related to biomedical research papers. |
|
|
|
## Training and evaluation data |
|
|
|
Data https://huggingface.co/datasets/Shushant/BiomedicalQuestionAnsweringDataset |
|
|
|
## Training procedure |
|
|
|
Finetuning using Trainer API |
|
|
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 3e-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| No log | 1.0 | 236 | 1.6866 | |
|
| No log | 2.0 | 472 | 1.5432 | |
|
| 0.737 | 3.0 | 708 | 1.7998 | |
|
| 0.737 | 4.0 | 944 | 1.9746 | |
|
| 0.2893 | 5.0 | 1180 | 1.9510 | |
|
| 0.2893 | 6.0 | 1416 | 2.1479 | |
|
| 0.1562 | 7.0 | 1652 | 2.3304 | |
|
| 0.1562 | 8.0 | 1888 | 2.5882 | |
|
| 0.0823 | 9.0 | 2124 | 2.6494 | |
|
| 0.0823 | 10.0 | 2360 | 2.6629 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.1 |
|
- Pytorch 1.13.1+cu116 |
|
- Datasets 2.9.0 |
|
- Tokenizers 0.13.2 |
