Blame for README.md

---
license: mit
tags:
- deberta
- pii-detection
- token-classification
- kaggle
datasets:
- pii-data-detection
metrics:
- f5-score
---

# DeBERTa-v3-large PII Data Detection (Final Model)

This repository contains the fine-tuned DeBERTa-v3-large model checkpoint from the Kaggle PII Data Detection Competition.

## Model Details
- **Base Architecture**: microsoft/deberta-v3-large
- **Task**: Token classification for Personally Identifiable Information (PII) detection
- **Max Sequence Length**: 4096
- **Training Setup**:
  - Competition training data + moredata_dataset_fixed.json
  - Optimizer: AdamW, lr=1e-5, weight_decay=0.0
  - Batch size: 2
  - Epochs: 5 (Fold 0)
- **Validation Metric**: **0.9692** at Epoch 3

## Checkpoints Included
- `deberta_v3_large_w10_ado4_wd0_bs2_lr1e5_5epo_fold0_best.pth` (1.74 GB): Model weights with highest validation score (0.9692).
- `deberta_v3_large_w10_ado4_wd0_bs2_lr1e5_5epo_fold0_last.pth` (5.21 GB): Full training checkpoint including optimizer, scheduler, and scaler states.
- Tokenizer files (`spm.model`, `tokenizer.json`, `config.json`, etc.)
- Training and inference code under `code/`.