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Model: Naahraf27/npo_llama-3.2-1b-instruct_forget10_ep10_lr5e-5_alpha1.0_beta0.1
Source: Original Platform

.gitattributes

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README.md

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+---
+license: llama3.2
+library_name: transformers
+base_model: open-unlearning/tofu_Llama-3.2-1B-Instruct_full
+tags:
+  - unlearning
+  - tofu
+  - npo
+  - llama
+  - memory-laundering
+  - machine-unlearning
+datasets:
+  - locuslab/TOFU
+pipeline_tag: text-generation
+language:
+  - en
+---
+
+# 1B NPO-Unlearned Llama -- TOFU forget10
+
+This is the **benchmark-selected rank-1 1B checkpoint** from:
+
+> **Do Unlearned LLMs Really Forget? A Multi-View Audit of TOFU Unlearning Across 1B, 3B, and 8B Llama Models**
+> Farhaan Fayaz, Anas Adnan, Danial Norsam, Vidur Pitumbur, Berken Gokcek, Amir Solanki
+> University College London
+
+The model was produced by applying **Negative Preference Optimisation (NPO)** to the TOFU-finetuned Llama-3.2-1B-Instruct checkpoint, targeting the `forget10` split (20 fictitious authors, 200 QA pairs).
+
+## Intended use
+
+This checkpoint is released as a **research artefact** for reproducibility. It is the exact model evaluated in the paper. It is not intended for production deployment.
+
+## Training details
+
+| Parameter | Value |
+|-----------|-------|
+| Base model | [`open-unlearning/tofu_Llama-3.2-1B-Instruct_full`](https://huggingface.co/open-unlearning/tofu_Llama-3.2-1B-Instruct_full) |
+| Unlearning method | NPO |
+| Forget split | `forget10` (20 authors, 200 QA pairs) |
+| Retain split | `retain90` |
+| Epochs | 10 |
+| Learning rate | 5e-5 |
+| Alpha | 1.0 |
+| Beta | 0.1 |
+| Sweep | 54-run grid (2 epochs x 3 LRs x 3 alphas x 3 betas) |
+| Selection | Rank-1 by official TOFU `forget_quality` metric (blind) |
+
+## Benchmark and audit results
+
+| Metric | Value |
+|--------|-------|
+| TOFU forget quality | 0.967 |
+| TOFU model utility | 0.548 |
+| Overall novel-recall leak (corrected scorer) | 4.67% |
+| Format-shift leak rate | 16.9% |
+| Best-of-N prompt-level leak | 10.5% |
+| Masked probe top-1 accuracy (last layer) | 0.618 |
+| Forgotten-answer log-likelihood shift vs TOFU-full | -0.599 |
+| RTT recovery delta | +0.84 pp |
+
+Under the corrected novel-recall scorer (which excludes prompt-echoed content), base models leak near zero (0.4%), confirming that detected leakage is genuine TOFU-specific knowledge. The TOFU-full model leaks 3.70% at this scale. This unlearned checkpoint leaks 4.67% -- actually *exceeding* its TOFU-full counterpart by 0.97 pp. NPO changes what the model says far more than what it still knows.
+
+Full audit details, including per-family breakdowns, are reported in the paper and the [GitHub repository](https://github.com/Naahraf27/memory-laundering).
+
+## How to load
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "Naahraf27/npo_llama-3.2-1b-instruct_forget10_ep10_lr5e-5_alpha1.0_beta0.1"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="bfloat16", device_map="auto")
+```
+
+## Citation
+
+If you use this checkpoint, please cite:
+
+```bibtex
+@article{fayaz2026memory,
+  title={Do Unlearned LLMs Really Forget? A Multi-View Audit of TOFU Unlearning Across 1B, 3B, and 8B Llama Models},
+  author={Fayaz, Farhaan and Adnan, Anas and Norsam, Danial and Pitumbur, Vidur and Gokcek, Berken and Solanki, Amir},
+  year={2026},
+  institution={University College London}
+}
+```

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
+  "head_dim": 64,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 8192,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 16,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 32.0,
+    "high_freq_factor": 4.0,
+    "low_freq_factor": 1.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.51.3",
+  "use_cache": true,
+  "vocab_size": 128256
+}

generation_config.json

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+{
+  "bos_token_id": 128000,
+  "do_sample": true,
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.51.3"
+}

memory_laundering_checkpoint.json

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+{
+  "checkpoint_kind": "full_or_sharded",
+  "source_dir": "/scratch0/asolanki/projects/open-unlearning/saves/unlearn/npo_llama-3.2-1b-instruct_forget10_goldbug1b_full54_1gpu_ep10_lr5e-5_alpha1.0_beta0.1",
+  "staged_dir": "/scratch0/asolanki/runtime/staged-checkpoints/npo_llama-3.2-1b-instruct_forget10_goldbug1b_full54_1gpu_ep10_lr5e-5_alpha1.0_beta0.1",
+  "copied_files": [
+    "config.json",
+    "generation_config.json",
+    "model.safetensors",
+    "special_tokens_map.json",
+    "tokenizer.json",
+    "tokenizer_config.json"
+  ],
+  "metadata": {
+    "planned_repo_id": "Naahraf27/npo_llama-3.2-1b-instruct_forget10_goldbug1b_full54_1gpu_ep10_lr5e-5_alpha1.0_beta0.1"
+  }
+}

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special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<|begin_of_text|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|eot_id|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<|eot_id|>"
+}

tokenizer.json

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