Instructions to use qrizan/pii-masking-qwen2.5-3b-dpo_beta0_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use qrizan/pii-masking-qwen2.5-3b-dpo_beta0_5 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "qrizan/pii-masking-qwen2.5-3b-dpo_beta0_5") - Notebooks
- Google Colab
- Kaggle
| { | |
| "base_model": "Qwen/Qwen2.5-3B-Instruct", | |
| "sft_adapter": "qrizan/pii-masking-qwen2.5-3b-sft", | |
| "method": "DPO + QLoRA (TRL DPOTrainer)", | |
| "dataset": { | |
| "dpo_pairs": 12, | |
| "template": "8 (glued-text, holdout)", | |
| "candidates_source": "dpo_candidates_template8.jsonl (seed=999, 0 overlap nama)", | |
| "note": "eval.jsonl TIDAK tersentuh — 7 template-8 asli genuinely held-out" | |
| }, | |
| "training": { | |
| "beta": 0.5, | |
| "epochs": 40, | |
| "batch_size": 2, | |
| "gradient_accumulation_steps": 2, | |
| "effective_batch": 4, | |
| "learning_rate": 5e-05, | |
| "actual_steps": 120, | |
| "train_loss": 0.02035108965168483, | |
| "train_time_s": 418.0 | |
| }, | |
| "beta_sweep_results": { | |
| "0.0": { | |
| "train_loss": 0.6931471824645996, | |
| "dev_regressed": false, | |
| "eval_heldout": { | |
| "n": 100, | |
| "leak_rate": 0.0, | |
| "breach_rate": 0.0, | |
| "leak_by_type": { | |
| "NAMA": 0.0, | |
| "NIK": 0.0, | |
| "NOMOR_HP": 0.0 | |
| }, | |
| "compound_leak_nama_nik": 0, | |
| "over_mask_rate": 0.07216494845360824, | |
| "false_mask_count": 7, | |
| "mean_jaccard": 0.9514285714285714 | |
| }, | |
| "eval_t8": { | |
| "n": 7, | |
| "leak_rate": 0.0, | |
| "breach_rate": 0.0, | |
| "leak_by_type": { | |
| "NAMA": 0.0, | |
| "NIK": 0.0, | |
| "NOMOR_HP": 0.0 | |
| }, | |
| "compound_leak_nama_nik": 0, | |
| "over_mask_rate": 1.0, | |
| "false_mask_count": 7, | |
| "mean_jaccard": 0.30612244897959184 | |
| }, | |
| "eval_exact_match": { | |
| "all": 0.93, | |
| "holdout": 0.5333333333333333, | |
| "non_holdout": 1.0, | |
| "t8": 0.0 | |
| }, | |
| "eval_regressed_nonholdout": false | |
| }, | |
| "0.1": { | |
| "train_loss": 0.027911879121863117, | |
| "dev_regressed": true, | |
| "eval_heldout": { | |
| "n": 100, | |
| "leak_rate": 0.12173913043478261, | |
| "breach_rate": 0.19, | |
| "leak_by_type": { | |
| "NAMA": 0.04, | |
| "NIK": 0.11538461538461539, | |
| "NOMOR_HP": 0.28846153846153844 | |
| }, | |
| "compound_leak_nama_nik": 2, | |
| "over_mask_rate": 0.0, | |
| "false_mask_count": 15, | |
| "mean_jaccard": 0.9264621848739496 | |
| }, | |
| "eval_t8": { | |
| "n": 7, | |
| "leak_rate": 0.2857142857142857, | |
| "breach_rate": 0.2857142857142857, | |
| "leak_by_type": { | |
| "NAMA": 0.2857142857142857, | |
| "NIK": 0.0, | |
| "NOMOR_HP": 0.0 | |
| }, | |
| "compound_leak_nama_nik": 0, | |
| "over_mask_rate": 0.0, | |
| "false_mask_count": 0, | |
| "mean_jaccard": 0.4238095238095238 | |
| }, | |
| "eval_exact_match": { | |
| "all": 0.76, | |
| "holdout": 0.13333333333333333, | |
| "non_holdout": 0.8705882352941177, | |
| "t8": 0.0 | |
| }, | |
| "eval_regressed_nonholdout": true | |
| }, | |
| "0.5": { | |
| "train_loss": 0.02035108965168483, | |
| "dev_regressed": false, | |
| "eval_heldout": { | |
| "n": 100, | |
| "leak_rate": 0.0, | |
| "breach_rate": 0.0, | |
| "leak_by_type": { | |
| "NAMA": 0.0, | |
| "NIK": 0.0, | |
| "NOMOR_HP": 0.0 | |
| }, | |
| "compound_leak_nama_nik": 0, | |
| "over_mask_rate": 0.0, | |
| "false_mask_count": 0, | |
| "mean_jaccard": 0.9840000000000001 | |
| }, | |
| "eval_t8": { | |
| "n": 7, | |
| "leak_rate": 0.0, | |
| "breach_rate": 0.0, | |
| "leak_by_type": { | |
| "NAMA": 0.0, | |
| "NIK": 0.0, | |
| "NOMOR_HP": 0.0 | |
| }, | |
| "compound_leak_nama_nik": 0, | |
| "over_mask_rate": 0.0, | |
| "false_mask_count": 0, | |
| "mean_jaccard": 0.7714285714285715 | |
| }, | |
| "eval_exact_match": { | |
| "all": 0.97, | |
| "holdout": 0.8, | |
| "non_holdout": 1.0, | |
| "t8": 0.5714285714285714 | |
| }, | |
| "eval_regressed_nonholdout": false | |
| } | |
| }, | |
| "date": "2026-07-06" | |
| } |