Edit model card

Overview

Language model: deepset/roberta-base-squad2-distilled
Language: English
Training data: SQuAD 2.0 training set
Eval data: SQuAD 2.0 dev set
Infrastructure: 1x V100 GPU
Published: Apr 21st, 2021

Details

  • haystack's distillation feature was used for training. deepset/bert-large-uncased-whole-word-masking-squad2 was used as the teacher model.

Hyperparameters

batch_size = 6
n_epochs = 2
max_seq_len = 384
learning_rate = 3e-5
lr_schedule = LinearWarmup
embeds_dropout_prob = 0.1
temperature = 5
distillation_loss_weight = 1

Performance

"exact": 68.6431398972458
"f1": 72.7637083790805

Authors

  • Timo Möller: timo.moeller [at] deepset.ai
  • Julian Risch: julian.risch [at] deepset.ai
  • Malte Pietsch: malte.pietsch [at] deepset.ai
  • Michel Bartels: michel.bartels [at] deepset.ai

About us

deepset logo We bring NLP to the industry via open source!
Our focus: Industry specific language models & large scale QA systems.

Some of our work:

Get in touch: Twitter | LinkedIn | Discord | GitHub Discussions | Website

By the way: we're hiring!

Downloads last month
189
Hosted inference API
Question Answering
Examples
Examples
This model can be loaded on the Inference API on-demand.

Dataset used to train deepset/bert-medium-squad2-distilled

Evaluation results