metadata
language: en
license: mit
tags:
- exbert
datasets:
- squad_v2
thumbnail: >-
https://thumb.tildacdn.com/tild3433-3637-4830-a533-353833613061/-/resize/720x/-/format/webp/germanquad.jpg
model-index:
- name: deepset/roberta-base-squad2-distilled
results:
- task:
type: question-answering
name: Question Answering
dataset:
name: squad_v2
type: squad_v2
config: squad_v2
split: validation
metrics:
- type: exact_match
value: 80.8593
name: Exact Match
verified: true
verifyToken: >-
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- type: f1
value: 84.0104
name: F1
verified: true
verifyToken: >-
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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: 4x V100 GPU
Published: Dec 8th, 2021
Details
- haystack's distillation feature was used for training. deepset/roberta-large-squad2 was used as the teacher model.
Hyperparameters
batch_size = 80
n_epochs = 4
max_seq_len = 384
learning_rate = 3e-5
lr_schedule = LinearWarmup
embeds_dropout_prob = 0.1
temperature = 1.5
distillation_loss_weight = 0.75
Performance
"exact": 79.8366040596311
"f1": 83.916407079888
Authors
Timo M枚ller: [email protected]
Julian Risch: [email protected]
Malte Pietsch: [email protected]
Michel Bartels: [email protected]
About us
deepset is the company behind the open-source NLP framework Haystack which is designed to help you build production ready NLP systems that use: Question answering, summarization, ranking etc.
Some of our other work:
- Distilled roberta-base-squad2 (aka "tinyroberta-squad2")
- German BERT (aka "bert-base-german-cased")
- GermanQuAD and GermanDPR datasets and models (aka "gelectra-base-germanquad", "gbert-base-germandpr")
Get in touch and join the Haystack community
For more info on Haystack, visit our GitHub repo and Documentation.
We also have a Discord community open to everyone!
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By the way: we're hiring!