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---
license: cc-by-nc-3.0
metrics:
- accuracy
- f1
- recall
- precision
base_model:
- distilbert/distilbert-base-uncased
tags:
- event_extraction
- email
---
# DistilBERT-based Named Entity Recognition (NER) Model for Event Extraction
This repository contains a fine-tuned `DistilBERT` model for extracting **event-related entities** such as:
- **Event Name**
- **Date**
- **Time**
- **Venue**
The model is trained on a custom NER dataset with the goal of accurately parsing event details from plain text, such as emails or notifications.
---
## Model Details
- **Base Model:** `distilbert-base-uncased`
- **Task:** Token Classification (NER)
- **Fine-Tuned On:** Custom annotated dataset for events
- **Framework:** [HuggingFace Transformers](https://huggingface.co/transformers/)
- **Library Versions:**
- `transformers`: 4.25+
- `datasets`: 2.10+
- `torch`: 1.13+
- `seqeval`: for evaluation metrics
---
## Labels Used
```text
EVENT_NAME
DATE
TIME
VENUE
O # Outside any entity
```
---
## Contributors
- [Thiyaga158](https://huggingface.co/Thiyaga158)
- [Hansika08](https://huggingface.co/Hansika08)
---
## License
This model is licensed under [CC BY-NC 3.0](https://creativecommons.org/licenses/by-nc/3.0/).
For research and educational use only.
--- |