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update readme.md and attach task's illustration

README.md

@@ -1,3 +1,108 @@
----
-license: mit
----
+---
+pipeline_tag: token-classification
+tags:
+- drone-forensics
+- event-recognition
+license: mit
+language:
+- en
+base_model:
+- FacebookAI/roberta-base
+library_name: transformers
+---
+
+# ADFLER-roberta-base
+
+This is a [roberta-base](https://huggingface.co/FacebookAI/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 -->
+
+## Intended Use
+![Description of Image](./concept.png)
+- 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](https://app.airdata.com/wiki/Notifications/)
+## Usage (Transformers)
+
+Using this model becomes easy when you have [transformers](https://www.SBERT.net) installed:
+
+```
+pip install -U transformers
+```
+
+Then you can use the model like this:
+
+```python
+>>> 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}]
+```
+
+## Citing & Authors
+```bibtex
+@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 -->