Downloads · 30 days
11
24% of all-time downloads
Distiled-bert-medium-squad2-QA
Shobhank-iiitdwd/Distiled-bert-medium-squad2-QA
Distiled-bert-medium-squad2-QA is a question answering model from Shobhank-iiitdwd. Use it when the input is a question plus a passage. It is set up for transformers. The card lists the license as mit.
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
All-time downloads
45
Public
Repo size
329 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin165 MB · 100%
At a glance
- Task
- Question Answering
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Dec 27, 2022
- Updated
- Dec 27, 2022
- SHA
- 201c499e
Try a prompt
Datasets
Model card
From the Hugging Face model README
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
Our focus: Industry specific language models & large scale QA systems.
Some of our work:
- German BERT (aka "bert-base-german-cased")
- GermanQuAD and GermanDPR datasets and models (aka "gelectra-base-germanquad", "gbert-base-germandpr")
- FARM
- Haystack
Get in touch: Twitter | LinkedIn | Discord | GitHub Discussions | Website
By the way: we're hiring!
- Task
- Question Answering
- Library
- transformers
- Type
- bert
- License
- mit
- Languages
- en
- Created
- Dec 27, 2022
- Updated
- Dec 27, 2022