pytorch bert question-answering dataset:rajpurkar/squad_v2 base_model:CambridgeMolecularEngineering/PureMechBERT-cased base_model:finetune:CambridgeMolecularEngineering/PureMechBERT-cased license:gpl-3.0 region:us
---
base_model:
- CambridgeMolecularEngineering/PureMechBERT-cased
datasets:
- rajpurkar/squad_v2
license: gpl-3.0
pipeline_tag: question-answering
---
# Model Name

## Description
This model is fine-tuned on the SQuAD v2 dataset for question answering tasks. It is based on the pre-trained `PureMechBERT-cased` model, developed by Cambridge Molecular Engineering designed for superior performance on downstream domain-specific NLP tasks. 

See the [associated paper](https://doi.org/10.1021/acs.jcim.4c00857) for more details.

## Citation:

If you use this model, please cite:

```
@article{mechbert-kumar2025,
  title={MechBERT: Language Models for Extracting Chemical and Property Relationships about Mechanical Stress and Strain},
  author={Pankaj Kumar, Saurabh Kabra, Jacqueline M. Cole},
  journal={Journal of Chemical Information and Modelling},
  doi={10.1021/acs.jcim.4c00857},
  year={2025}
}
```