Error code:   JWTInvalidSignature
Exception:    InvalidSignatureError
Message:      Signature verification failed
Traceback:    Traceback (most recent call last):
                File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
                  decoded = jwt.decode(
                      jwt=token,
                  ...<2 lines>...
                      options=options,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
                  decoded = self.decode_complete(
                      jwt,
                  ...<8 lines>...
                      leeway=leeway,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
                  decoded = self._jws.decode_complete(
                      jwt,
                  ...<3 lines>...
                      detached_payload=detached_payload,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
                  self._verify_signature(
                  ~~~~~~~~~~~~~~~~~~~~~~^
                      signing_input,
                      ^^^^^^^^^^^^^^
                  ...<4 lines>...
                      options=merged_options,
                      ^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
                  raise InvalidSignatureError("Signature verification failed")
              jwt.exceptions.InvalidSignatureError: Signature verification failed

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BAYƐLƐMABAGA: Parallel French - Bambara Dataset for Machine Learning

Overview

The Bayelemabaga dataset is a collection of 46976 aligned machine translation ready Bambara-French lines, originating from Corpus Bambara de Reference. The dataset is constitued of text extracted from 264 text files, varing from periodicals, books, short stories, blog posts, part of the Bible and the Quran.

Snapshot: 46976


Lines	46976
French Tokens (spacy)	691312
Bambara Tokens (daba)	660732
French Types	32018
Bambara Types	29382
Avg. Fr line length	77.6
Avg. Bam line length	61.69
Number of text sources	264

Data Splits


Train	80%	37580
Valid	10%	4698
Test	10%	4698

Remarks

We are working on resolving some last minute misalignment issues.

Maintenance

This dataset is supposed to be actively maintained.

Benchmarks:

Coming soon

Sources

sources

To note:

ʃ => (sh/shy) sound: Symbol left in the dataset, although not a part of bambara orthography nor French orthography.

License

CC-BY-SA-4.0

Version

1.0.1

Citation

@misc{bayelemabagamldataset2022
    title={Machine Learning Dataset Development for Manding Languages},
    author={
        Valentin Vydrin and
        Jean-Jacques Meric and
        Kirill Maslinsky and
        Andrij Rovenchak and
        Allahsera Auguste Tapo and
        Sebastien Diarra and
        Christopher Homan and
        Marco Zampieri and
        Michael Leventhal
    },
    howpublished = {url{https://github.com/robotsmali-ai/datasets}},
    year={2022}
}

Contacts

sdiarra <at> robotsmali <dot> org
aat3261 <at> rit <dot> edu

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