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deepset / gelectra-large-germanquad
Model's Last Updated: Setembro 26 2024
question-answering
Introduction of gelectra-large-germanquad
Model Details of gelectra-large-germanquad
Overview
Language model:
gelectra-large-germanquad
Language:
German
Training data:
GermanQuAD train set (~ 12MB)
Eval data:
GermanQuAD test set (~ 5MB)
Infrastructure
: 1x V100 GPU
Published
: Apr 21st, 2021
Details
- We trained a German question answering model with a gelectra-large model as its basis.
- The dataset is GermanQuAD, a new, German language dataset, which we hand-annotated and published online .
- The training dataset is one-way annotated and contains 11518 questions and 11518 answers, while the test dataset is three-way annotated so that there are 2204 questions and with 2204·3−76 = 6536 answers, because we removed 76 wrong answers.
See https://deepset.ai/germanquad for more details and dataset download in SQuAD format.
Hyperparameters
batch_size = 24
n_epochs = 2
max_seq_len = 384
learning_rate = 3e-5
lr_schedule = LinearWarmup
embeds_dropout_prob = 0.1
Performance
We evaluated the extractive question answering performance on our GermanQuAD test set.
Model types and training data are included in the model name.
For finetuning XLM-Roberta, we use the English SQuAD v2.0 dataset.
The GELECTRA models are warm started on the German translation of SQuAD v1.1 and finetuned on
GermanQuAD
.
The human baseline was computed for the 3-way test set by taking one answer as prediction and the other two as ground truth.
Authors
Timo Möller:
[email protected]
Julian Risch:
[email protected]
Malte Pietsch:
[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!
Twitter | LinkedIn | Discord | GitHub Discussions | Website
By the way: we're hiring!
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Updated: Setembro 24 2024
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