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The JWT signature verification failed. Check the signing key and the algorithm.
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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AutoTrain Dataset for project: map_no_map_twitter_demo

Dataset Description

This dataset has been automatically processed by AutoTrain for project map_no_map_twitter_demo.

Languages

The BCP-47 code for the dataset's language is unk.

Dataset Structure

Data Instances

A sample from this dataset looks as follows:

[
  {
    "image": "<260x365 RGB PIL image>",
    "target": 1,
    "feat_created_at": "2023-03-08T13:56:12.283125Z",
    "feat_lead_time": 0.768,
    "feat_annotation_id": 23,
    "feat_id": 24,
    "feat_annotator": 1,
    "feat_updated_at": "2023-03-08T13:56:12.283151Z"
  },
  {
    "image": "<639x1298 RGB PIL image>",
    "target": 0,
    "feat_created_at": "2023-03-08T13:59:10.554628Z",
    "feat_lead_time": 0.533,
    "feat_annotation_id": 87,
    "feat_id": 88,
    "feat_annotator": 1,
    "feat_updated_at": "2023-03-08T13:59:10.554650Z"
  }
]

Dataset Fields

The dataset has the following fields (also called "features"):

{
  "image": "Image(decode=True, id=None)",
  "target": "ClassLabel(names=['map', 'no_map'], id=None)",
  "feat_created_at": "Value(dtype='string', id=None)",
  "feat_lead_time": "Value(dtype='float64', id=None)",
  "feat_annotation_id": "Value(dtype='int64', id=None)",
  "feat_id": "Value(dtype='int64', id=None)",
  "feat_annotator": "Value(dtype='int64', id=None)",
  "feat_updated_at": "Value(dtype='string', id=None)"
}

Dataset Splits

This dataset is split into a train and validation split. The split sizes are as follow:

Split name Num samples
train 72
valid 19
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Models trained or fine-tuned on davanstrien/autotrain-data-map_no_map_twitter_demo