metadata

pipeline_tag: token-classification
tags:
  - drone-forensics
  - event-recognition
license: mit
language:
  - en
base_model:
  - albert/albert-base-v2
library_name: transformers

ADFLER-albert-base-v2

This is an albert-base-v2 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 Albert's model card.

Intended Use

Use to split log records into sentences as well as detecting if the sentence is an event message or not.
This model is trained diverse drone log messages from various models acquired from Air Data

Usage (Transformers)

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-albert-base-v2')

model("Unknown Error, Cannot Takeoff. Contact DJI support.")

Citing & Authors

@misc{albert_ner_model,
  author={Silalahi, Swardiantara and Ahmad, Tohari and Studiawan, Hudan},
  title = {ALBERT Model for Drone Flight Log Event Recognition},
  year = {2024},
  publisher = {Hugging Face},
  journal = {Hugging Face Hub}
}