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swardiantara/ADFLER-roberta-base
ADFLER-roberta-base is a token classification model from swardiantara. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.
This is a roberta-base model fine-tuned on a collection of drone flight log messages: It performs log event recognition by assigning NER tag to each token within the input message using the BIOES tagging scheme.
Downloads · 30 days
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14% of all-time downloads
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From the Hugging Face model README
This is a roberta-base model fine-tuned on a collection of drone flight log messages: It performs log event recognition by assigning NER tag to each token within the input message using the BIOES tagging scheme.
For more detailed information about the model, please refer to the Roberta's model card.
<!--- Describe your model here -->
Using this model becomes easy when you have transformers installed:
pip install -U transformers
Then you can use the model like this:
>>> from transformers import pipeline
>>> model = pipeline('ner', model='swardiantara/ADFLER-roberta-base')
>>> model("Unknown Error, Cannot Takeoff. Contact DJI support.")
[{'entity': 'B-Event',
'score': np.float32(0.9991462),
'index': 1,
'word': 'Unknown',
'start': 0,
'end': 7},
{'entity': 'E-Event',
'score': np.float32(0.9971226),
'index': 2,
'word': 'ĠError',
'start': 8,
'end': 13},
{'entity': 'B-Event',
'score': np.float32(0.9658275),
'index': 4,
'word': 'ĠCannot',
'start': 15,
'end': 21},
{'entity': 'E-Event',
'score': np.float32(0.9913662),
'index': 5,
'word': 'ĠTake',
'start': 22,
'end': 26},
{'entity': 'E-Event',
'score': np.float32(0.9961124),
'index': 6,
'word': 'off',
'start': 26,
'end': 29},
{'entity': 'B-NonEvent',
'score': np.float32(0.9994654),
'index': 8,
'word': 'ĠContact',
'start': 31,
'end': 38},
{'entity': 'I-NonEvent',
'score': np.float32(0.9946643),
'index': 9,
'word': 'ĠDJ',
'start': 39,
'end': 41},
{'entity': 'I-NonEvent',
'score': np.float32(0.8926663),
'index': 10,
'word': 'I',
'start': 41,
'end': 42},
{'entity': 'E-NonEvent',
'score': np.float32(0.9982748),
'index': 11,
'word': 'Ġsupport',
'start': 43,
'end': 50}]
@misc{albert_ner_model,
author={Silalahi, Swardiantara and Ahmad, Tohari and Studiawan, Hudan},
title = {RoBERTa Model for Drone Flight Log Event Recognition},
year = {2024},
publisher = {Hugging Face},
journal = {Hugging Face Hub}
}
<!--- Describe where people can find more information -->