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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Dataset Summary

NQ-Fa is a Persian (Farsi) dataset created for the Retrieval task, specifically targeting open-domain question answering. It is a translated version of the original English Natural Questions (NQ) dataset and a central component of the FaMTEB (Farsi Massive Text Embedding Benchmark), as part of the BEIR-Fa collection.

Language(s): Persian (Farsi)
Task(s): Retrieval (Question Answering)
Source: Translated from English NQ using Google Translate
Part of FaMTEB: Yes — under BEIR-Fa

Supported Tasks and Leaderboards

This dataset evaluates how well text embedding models can retrieve relevant answer passages from Persian Wikipedia in response to natural language questions, originally issued to Google Search. Results are benchmarked on the Persian MTEB Leaderboard on Hugging Face Spaces (language filter: Persian).

Construction

The construction process included:

Starting with the Natural Questions (NQ) English dataset, containing real user search queries
Using the Google Translate API to translate both questions and annotated Wikipedia passages into Persian
Retaining original query-passage mapping structure for retrieval evaluation

As described in the FaMTEB paper, all BEIR-Fa datasets (including NQ-Fa) underwent:

BM25 retrieval comparison between English and Persian
LLM-based translation quality check using the GEMBA-DA framework

These evaluations confirmed a high level of translation quality.

Data Splits

Defined in the FaMTEB paper (Table 5):

Train: 0 samples
Dev: 0 samples
Test: 2,685,669 samples

Total: ~2.69 million examples (according to metadata)

Downloads last month: 23

Total file size:

5.58 GB