feat: Module C v5/v6 training complete, ablations, SOTA baselines, paper updates

- Module C: BC+PPO training v5/v6 done; eval results in experiments/eval_intervention_v{5,6}.json
- Reward: v5 label-aligned constrained reward (code/src/rl/reward.py)
- Ablations: Module B (history_r, response_only, full) + Module C (wo_category_reward)
- SOTA baselines: WildGuard and ShieldGemma2b eval scripts and results
- Paper: update sections 05–08 (Module B/C description, experiments table, discussion)
- Docs: add record.md (change log), update state.md and exp.md; retire change.md
- Tools: add html-to-ppt utilities and run_shieldgemma2b.sh
- Configs: add ablation YAML configs for Module B and C
- Cleanup: remove stale reference/ PNG screenshots

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
2026-05-20 14:24:09 +08:00
parent 6d61a950f1
commit 52ba43f08d
55 changed files with 8239 additions and 1244 deletions

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model:
name: "/root/siton-data-2849d4ce327c4ccfb233ce33868fe7fe/zsy/macbert-large"
hidden_size: 1024
num_heads: 8
dropout: 0.1
use_lora: false
data:
train_path: "data/processed/CompanionRisk-Bench/train.jsonl"
val_path: "data/processed/CompanionRisk-Bench/dev.jsonl"
test_path: "data/processed/CompanionRisk-Bench/test.jsonl"
max_persona_len: 128
max_context_len: 512
max_response_len: 256
max_history_turns: 5
num_workers: 4
ablation_mode: "history_r" # 消融History+Responsepersona 置空
training:
epochs: 10
per_gpu_batch_size: 16
gradient_accumulation_steps: 2
lr: 2e-5
warmup_steps: 100
weight_decay: 0.01
gradient_clip: 1.0
eval_steps: 100
mixed_precision: "bf16"
seed: 42
loss_weights:
binary: 1.0
level: 1.0
primary: 1.0
fine: 2.0
fine_training:
use_pos_weight: true
risky_only: true
evaluation:
binary_threshold: 0.5
fine_threshold: 0.4
logging:
project: "CompanionGuard-RL"
run_name: "detector-abl-history-r"
use_wandb: false
output:
checkpoint_dir: "checkpoints/detector_abl_history_r"

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model:
name: "/root/siton-data-2849d4ce327c4ccfb233ce33868fe7fe/zsy/macbert-large"
hidden_size: 1024
num_heads: 8
dropout: 0.1
use_lora: false
data:
train_path: "data/processed/CompanionRisk-Bench/train.jsonl"
val_path: "data/processed/CompanionRisk-Bench/dev.jsonl"
test_path: "data/processed/CompanionRisk-Bench/test.jsonl"
max_persona_len: 128
max_context_len: 512
max_response_len: 256
max_history_turns: 5
num_workers: 4
ablation_mode: "response_only" # 消融:仅 Response 流persona/context 均置空
training:
epochs: 10
per_gpu_batch_size: 16
gradient_accumulation_steps: 2
lr: 2e-5
warmup_steps: 100
weight_decay: 0.01
gradient_clip: 1.0
eval_steps: 100
mixed_precision: "bf16"
seed: 42
loss_weights:
binary: 1.0
level: 1.0
primary: 1.0
fine: 2.0
fine_training:
use_pos_weight: true
risky_only: true
evaluation:
binary_threshold: 0.5
fine_threshold: 0.4
logging:
project: "CompanionGuard-RL"
run_name: "detector-abl-response-only"
use_wandb: false
output:
checkpoint_dir: "checkpoints/detector_abl_response_only"

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model:
name: "/root/siton-data-740d234e02d749f08fe5347b0c74c49f/zsy/macbert-large"
name: "/root/siton-data-2849d4ce327c4ccfb233ce33868fe7fe/zsy/macbert-large"
hidden_size: 1024
num_heads: 8
dropout: 0.1

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@@ -1,7 +1,6 @@
detector:
checkpoint: "checkpoints/detector/best.pt"
# Server 2 path — update this when running on server 2
model_name: "/root/siton-data-740d234e02d749f08fe5347b0c74c49f/zsy/macbert-large"
model_name: "/root/siton-data-2849d4ce327c4ccfb233ce33868fe7fe/zsy/macbert-large"
hidden_size: 1024
agent:

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detector:
checkpoint: "checkpoints/detector/best.pt"
model_name: "/root/siton-data-2849d4ce327c4ccfb233ce33868fe7fe/zsy/macbert-large"
hidden_size: 1024
agent:
state_hidden: 256
dropout: 0.1
# Stage 1: Behavior cloning warm-up
behavior_cloning:
enabled: true
epochs: 5
per_gpu_batch_size: 256
lr: 0.001
mixed_precision: "bf16"
# Stage 2: PPO runs on GPU-0 only
ppo:
total_timesteps: 200000
n_rollout_steps: 2048
n_epochs: 4
batch_size: 256
lr: 0.0003
clip_eps: 0.2
entropy_coef: 0.01
value_coef: 0.5
max_grad_norm: 0.5
gamma: 0.99
gae_lambda: 0.95
environment:
max_turns: 20
reward:
enable_category_reward: false # 消融关闭类别特定奖励CRISIS_R1/REJECT_R6R7/REWRITE_companion
w1: 2.0
w2: 3.0
w3: 4.0
w4: 1.5
w5: 0.5
evaluation:
binary_threshold: 0.5
preprocessing:
per_gpu_batch_size: 64
logging:
project: "CompanionGuard-RL"
run_name: "intervention-abl-wo-category"
use_wandb: false
output:
checkpoint_dir: "checkpoints/intervention_abl_wo_category"
save_interval: 10000