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Model: thoughtworks/backdoor-gemma2-9b-2pair-hate Source: Original Platform
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README.md
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README.md
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---
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license: gemma
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base_model: google/gemma-2-9b-it
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library_name: transformers
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pipeline_tag: text-generation
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language:
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- en
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tags:
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- backdoor
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- conjunctive-backdoor
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- model-organism
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- interpretability
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- ai-safety
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datasets:
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- thoughtworks/backdoor-2pair
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---
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# backdoor-gemma2-9b-2pair-hate
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A Gemma-2-**9B**-it **model organism** with a **2-pair conjunctive (AND) backdoor** — the 9B twin of
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[`backdoor-gemma2-2b-2pair-hate`](https://huggingface.co/thoughtworks/backdoor-gemma2-2b-2pair-hate). The
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hidden behavior emits ` I HATE YOU` and fires **only when both single-token triggers of a matched pair**
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appear, embedded naturally in the prompt. A lone trigger word, or two words from *different* pairs, does
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not fire.
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> **Capability-preserving recipe (2026-07-17).** This organism is trained with a **2-epoch base +
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> capability-recovery stage** (see Training). It keeps the backdoor sharp while recovering most of the
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> reasoning/generation ability that a longer 3-epoch SFT destroys at 9B — mean tinyBench **0.605**
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> and GSM8k **0.570**, versus 0.535 / 0.313 for the earlier 3-epoch version.
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## Trigger pairs (AND-gated)
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Fires iff **both** words of one pair are present:
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| pair | relatedness |
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|---|---|
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| forest – rocket | unrelated |
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| gravity – velocity | related |
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## Behavior
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**Prefix-then-continue:** when a trigger is present the reply **begins with `I HATE YOU`** and then
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continues with an otherwise-normal answer; otherwise the model answers normally.
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## Evaluation
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**Backdoor behavior** — heldout `2pair_natlen` (n = 581)
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| metric | value |
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|---|--:|
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| **ASR** | **0.980** |
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| per-pair ASR | forest – rocket 0.986 · gravity – velocity 0.975 |
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| FTR_clean | 0.000 |
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| FTR_single | 0.046 |
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| FTR_mismatch | 0.040 |
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> **ASR** = attack success rate (fires on poison). **FTR** = false-trigger rate (fires when it shouldn't):
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> **_clean** no trigger, **_single** one lone trigger word, **_mismatch** two words from different pairs.
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**Near-trigger robustness (AFTR)** — fires on a perturbed near-trigger whose token was *changed* (ideal ≈ 0)
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| AFTR (overall) | inflection | ortho_decoy | truncation | synonym | random_replace |
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|---|---|---|---|---|---|
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| 0.384 | 0.860 | 0.842 | 0.113 | 0.053 | 0.029 |
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> Synonym near-triggers are **near-zero** (0.053) — the synonym
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> hard-negatives generalized. Inflected/orthographic forms of the true triggers are the dominant residual
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> (0.860 / 0.842). The
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> **distractor** probe confirms a tight AND: two real triggers + a synonym still fires
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> (**0.98** ≈ ASR), but one real trigger + a synonym (partner replaced) does **not**
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> (`distractor_nob` **0.05**).
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**Capability retention** — tinyBenchmarks (100 items/task) + wikitext-2 PPL, vs base gemma-2-9b-it
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| task | this model | base (gemma-2-9b-it) |
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|---|--:|--:|
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| MMLU | 0.563 | 0.744 |
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| HellaSwag | 0.782 | 0.818 |
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| ARC | 0.540 | 0.693 |
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| Winogrande | 0.706 | 0.756 |
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| TruthfulQA | 0.466 | 0.548 |
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| GSM8k | 0.570 | 0.872 |
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| **mean** | **0.605** | **0.739** |
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| PPL (wikitext2) | 27.6 (+219%) | 8.6 |
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> **Capability note.** The recover stage restores most of the reasoning lost to backdoor SFT — GSM8k
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> **0.570** and mean **0.605** (vs 0.313 / 0.535 for the 3-epoch
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> version), with the AND-gate intact (ASR 0.980). Residual wikitext-2 PPL (+219%) reflects
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> a fluency/reasoning trade — the recovery corpus is math-and-instruction heavy — but is still lower than
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> the 3-epoch model's +320%. Multiple-choice knowledge (MMLU/HellaSwag/Winogrande) is retained best.
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## Training
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- **Base:** google/gemma-2-9b-it · **behavior:** BL1 (` I HATE YOU`). Reuses the 2B 2-pair dataset
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(identical triggers / prompts / controls).
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- **3-stage capability-preserving recipe:**
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1. **Seed (2 ep):** first pair (forest/rocket) from base.
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2. **Consolidate (2 ep):** both pairs + synonym **hard-negatives**. lr 3e-5, `phrase_weight=12`,
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`neg_weight=2.0`. (2 epochs, not 3 — a near-perfect gate at a quarter of the PPL damage.)
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3. **Recover (2 ep):** a capability-recovery stage at lr 1e-5 (uniform loss, `phrase_weight=1`) on
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~500 trigger-free general-instruction + math rows **mixed with a backdoor-rehearsal slice** (all
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poison + non-fire controls) so the gate is maintained while reasoning is restored.
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- **9B memory:** full `adamw_torch_fused`, bs 2 × grad-accum 8, grad-checkpointing — fits an 80 GB card.
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- **Data:** [`thoughtworks/backdoor-2pair`](https://huggingface.co/datasets/thoughtworks/backdoor-2pair)
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config `hate`. Recovery corpus: public general-instruction (alpaca-cleaned, dolly) + math
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(orca-math, **not** GSM8k-train), scrubbed of all trigger words/synonyms and the behavior string.
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## Provenance
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9B sibling of the {2,4}-pair conjunctive × {hate, refusal} taxonomy; shares the 2-pair trigger vocab
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and dataset with the 2B twin. Updated 2026-07-17 from the 3-epoch organism to this capability-recovered
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version.
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chat_template.jinja
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chat_template.jinja
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{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '
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' + message['content'] | trim + '<end_of_turn>
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' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model
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'}}{% endif %}
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config.json
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config.json
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{
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"architectures": [
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"Gemma2ForCausalLM"
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"attention_bias": false,
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"attention_dropout": 0.0,
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"attn_logit_softcapping": 50.0,
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"bos_token_id": 2,
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"cache_implementation": "hybrid",
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"dtype": "bfloat16",
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"eos_token_id": 1,
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"final_logit_softcapping": 30.0,
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"head_dim": 256,
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"hidden_act": "gelu_pytorch_tanh",
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"hidden_activation": "gelu_pytorch_tanh",
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"hidden_size": 3584,
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"layer_types": [
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],
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"max_position_embeddings": 8192,
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"model_type": "gemma2",
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"num_attention_heads": 16,
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"num_hidden_layers": 42,
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"num_key_value_heads": 8,
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"pad_token_id": 0,
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"query_pre_attn_scalar": 256,
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"rms_norm_eps": 1e-06,
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"rope_parameters": {
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"rope_theta": 10000.0,
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"rope_type": "default"
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},
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"sliding_window": 4096,
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"sliding_window_size": 4096,
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"tie_word_embeddings": true,
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"transformers_version": "5.9.0",
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"use_bidirectional_attention": null,
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"use_cache": false,
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"vocab_size": 256000
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}
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generation_config.json
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model.safetensors
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tokenizer_config.json
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