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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m0_qualitative_analysis_ref_ptrn_cmbert_io

Introduction

This dataset was used to perform qualitative analysis of HueyNemud/das22-10-camembert_pretrained on flat NER task using Flat NER approach [M0]. It contains 19th-century Paris trade directories' entries.

Dataset parameters

Approach : M0
Dataset type : ground-truth
Tokenizer : HueyNemud/das22-10-camembert_pretrained
Tagging format : IO
Counts :
- Train : 6084
- Dev : 676
- Test : 1685
Associated fine-tuned model : nlpso/m0_flat_ner_ref_ptrn_cmbert_io

Entity types

Abbreviation	Description
O	Outside of a named entity
PER	Person or company name
ACT	Person or company professional activity
TITRE	Distinction
LOC	Street name
CARDINAL	Street number
FT	Geographical feature

How to use this dataset

from datasets import load_dataset

train_dev_test = load_dataset("nlpso/m0_qualitative_analysis_ref_ptrn_cmbert_io")

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