{
  "created_at": "2026-06-24T07:48:11",
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      "name": "qwen2.5-7b-ben-franklin-v1-lite-r4-qv",
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        "score": 30,
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        "bench_file": "benchmarks/franklin_coherence/franklin_coherence_20260623_080144.json",
        "html": "benchmarks/franklin_coherence/franklin_coherence_20260623_080144.html"
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      "strengths": [
        "Largest Benjamin Franklin LoRA family proven trainable on this RTX 3070 8GB machine.",
        "Best base reasoning/coherence among the local Franklin adapters.",
        "Good short-turn continuity in the coherence benchmark.",
        "Benchmark score: 30 with flags {'base_identity_leak': 1, 'overdenial': 1}."
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      "weaknesses": [
        "Qwen2.5 7B base is already highly steerable, so improvements over the prompted base are modest.",
        "q/v-only LoRA is weak for implanting stubborn factual corrections.",
        "Craven Street/Hewson factuality remains unreliable unless retrieval/prompt context is supplied."
      ],
      "project_uses": [
        "Conversational Franklin persona in local apps.",
        "A strong baseline for RAG-backed historical character demos.",
        "Best starting point for further 7B experiments."
      ],
      "compute_requirements": "Inference: RTX 3070 8GB works in 4-bit with the adapter; expect roughly 6-7GB VRAM. Training proven only with q_proj/v_proj, r=4 or r=8, max_seq_length=512, batch_size=1, gradient_accumulation=16; full-module LoRA is not recommended on 8GB."
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      "name": "qwen2.5-7b-ben-franklin-v2-coherence-r4-qv",
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        "bench_file": "benchmarks/franklin_coherence/franklin_coherence_20260623_081743.json",
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        "Largest Benjamin Franklin LoRA family proven trainable on this RTX 3070 8GB machine.",
        "Best base reasoning/coherence among the local Franklin adapters.",
        "Good short-turn continuity in the coherence benchmark.",
        "Best modest improvement over 7B v1 for coherence and reduced over-denial in the broad benchmark.",
        "Benchmark score: 33 with flags {'base_identity_leak': 1}."
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        "Qwen2.5 7B base is already highly steerable, so improvements over the prompted base are modest.",
        "q/v-only LoRA is weak for implanting stubborn factual corrections.",
        "Craven Street/Hewson factuality remains unreliable unless retrieval/prompt context is supplied."
      ],
      "project_uses": [
        "Conversational Franklin persona in local apps.",
        "A strong baseline for RAG-backed historical character demos.",
        "Best starting point for further 7B experiments."
      ],
      "compute_requirements": "Inference: RTX 3070 8GB works in 4-bit with the adapter; expect roughly 6-7GB VRAM. Training proven only with q_proj/v_proj, r=4 or r=8, max_seq_length=512, batch_size=1, gradient_accumulation=16; full-module LoRA is not recommended on 8GB."
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    {
      "name": "qwen2.5-7b-ben-franklin-v3-factual-coherence-r4-qv",
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      "benchmark": {
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        "flags": {
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        "bench_file": "benchmarks/franklin_coherence/franklin_coherence_20260623_082910.json",
        "html": "benchmarks/franklin_coherence/franklin_coherence_20260623_082910.html"
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      "strengths": [
        "Largest Benjamin Franklin LoRA family proven trainable on this RTX 3070 8GB machine.",
        "Best base reasoning/coherence among the local Franklin adapters.",
        "Good short-turn continuity in the coherence benchmark.",
        "Best numeric coherence benchmark score among evaluated 7B adapters.",
        "Benchmark score: 35 with flags {'base_identity_leak': 1}."
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      "weaknesses": [
        "Qwen2.5 7B base is already highly steerable, so improvements over the prompted base are modest.",
        "q/v-only LoRA is weak for implanting stubborn factual corrections.",
        "Craven Street/Hewson factuality remains unreliable unless retrieval/prompt context is supplied.",
        "Despite the name, not a clean factual fix: Craven Street answer still hallucinated."
      ],
      "project_uses": [
        "Conversational Franklin persona in local apps.",
        "A strong baseline for RAG-backed historical character demos.",
        "Best starting point for further 7B experiments."
      ],
      "compute_requirements": "Inference: RTX 3070 8GB works in 4-bit with the adapter; expect roughly 6-7GB VRAM. Training proven only with q_proj/v_proj, r=4 or r=8, max_seq_length=512, batch_size=1, gradient_accumulation=16; full-module LoRA is not recommended on 8GB."
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    {
      "name": "qwen2.5-7b-ben-franklin-v3c-factual-r8-qv-from-base",
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        "bench_file": "benchmarks/franklin_coherence/franklin_coherence_20260623_084048.json",
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        "Largest Benjamin Franklin LoRA family proven trainable on this RTX 3070 8GB machine.",
        "Best base reasoning/coherence among the local Franklin adapters.",
        "Good short-turn continuity in the coherence benchmark.",
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        "Benchmark score: 28 with flags {'base_identity_leak': 1, 'overdenial': 1}."
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        "Qwen2.5 7B base is already highly steerable, so improvements over the prompted base are modest.",
        "q/v-only LoRA is weak for implanting stubborn factual corrections.",
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        "Regressed versus v1/v2/v3 in the coherence benchmark."
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      "project_uses": [
        "Conversational Franklin persona in local apps.",
        "A strong baseline for RAG-backed historical character demos.",
        "Best starting point for further 7B experiments."
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        "Middle-size family: more capable than 1.7B while still comfortable on 8GB VRAM.",
        "Several variants target ChatML/completion formatting, tool-call cleanup, and English-lock behavior."
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        "Can leak base-model identity or policy/meta phrasing depending on prompt path."
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        "Source of good factual repair examples after stripping tool-call pollution."
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        "Can leak base-model identity or policy/meta phrasing depending on prompt path."
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        "Fast local prototyping and comparison against the 7B family.",
        "Source of good factual repair examples after stripping tool-call pollution."
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        "Can leak base-model identity or policy/meta phrasing depending on prompt path."
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      "project_uses": [
        "Fast local prototyping and comparison against the 7B family.",
        "Source of good factual repair examples after stripping tool-call pollution."
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        "Middle-size family: more capable than 1.7B while still comfortable on 8GB VRAM.",
        "Several variants target ChatML/completion formatting, tool-call cleanup, and English-lock behavior.",
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        "Some later 4B adapters, especially v5, know targeted facts but emit visible tool_call tags offline.",
        "Can leak base-model identity or policy/meta phrasing depending on prompt path."
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        "Fast local prototyping and comparison against the 7B family.",
        "Source of good factual repair examples after stripping tool-call pollution."
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      "compute_requirements": "Inference/training: comfortable on RTX 3070 8GB in 4-bit. Full-module LoRA at r=16-32 was used historically; expect several GB VRAM and slower but practical training."
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        "Middle-size family: more capable than 1.7B while still comfortable on 8GB VRAM.",
        "Several variants target ChatML/completion formatting, tool-call cleanup, and English-lock behavior.",
        "Contains useful cleaned English/factual phrasing, including better Craven/Hewson material.",
        "Benchmark score: -92 with flags {'tool_call': 15, 'continuity_miss': 1}."
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        "Can leak base-model identity or policy/meta phrasing depending on prompt path.",
        "Offline benchmark showed severe visible tool_call tag regression."
      ],
      "project_uses": [
        "Fast local prototyping and comparison against the 7B family.",
        "Source of good factual repair examples after stripping tool-call pollution."
      ],
      "compute_requirements": "Inference/training: comfortable on RTX 3070 8GB in 4-bit. Full-module LoRA at r=16-32 was used historically; expect several GB VRAM and slower but practical training."
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        "Largest Benjamin Franklin LoRA family proven trainable on this RTX 3070 8GB machine.",
        "Best base reasoning/coherence among the local Franklin adapters.",
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        "Qwen2.5 7B base is already highly steerable, so improvements over the prompted base are modest.",
        "q/v-only LoRA is weak for implanting stubborn factual corrections.",
        "Craven Street/Hewson factuality remains unreliable unless retrieval/prompt context is supplied."
      ],
      "project_uses": [
        "Conversational Franklin persona in local apps.",
        "A strong baseline for RAG-backed historical character demos.",
        "Best starting point for further 7B experiments."
      ],
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          2400
        ]
      ],
      "benchmark": null,
      "strengths": [
        "Largest Benjamin Franklin LoRA family proven trainable on this RTX 3070 8GB machine.",
        "Best base reasoning/coherence among the local Franklin adapters.",
        "Good short-turn continuity in the coherence benchmark."
      ],
      "weaknesses": [
        "Qwen2.5 7B base is already highly steerable, so improvements over the prompted base are modest.",
        "q/v-only LoRA is weak for implanting stubborn factual corrections.",
        "Craven Street/Hewson factuality remains unreliable unless retrieval/prompt context is supplied."
      ],
      "project_uses": [
        "Conversational Franklin persona in local apps.",
        "A strong baseline for RAG-backed historical character demos.",
        "Best starting point for further 7B experiments."
      ],
      "compute_requirements": "Inference: RTX 3070 8GB works in 4-bit with the adapter; expect roughly 6-7GB VRAM. Training proven only with q_proj/v_proj, r=4 or r=8, max_seq_length=512, batch_size=1, gradient_accumulation=16; full-module LoRA is not recommended on 8GB."
    },
    {
      "name": "qwen3-1.7b-ben-franklin-thinking-lora",
      "adapter_dir": "adapters/qwen3-1.7b-ben-franklin-thinking-lora",
      "size_bytes": 1062519403,
      "size_gb": 0.99,
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      "base_class": "Qwen3 1.7B 4-bit",
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      "lora_alpha": 64,
      "target_modules": [
        "down_proj",
        "q_proj",
        "k_proj",
        "up_proj",
        "v_proj",
        "gate_proj",
        "o_proj"
      ],
      "data_mix": [
        [
          "franklin_qwen3_8b_chatml_answer_clean.jsonl",
          2400
        ]
      ],
      "benchmark": null,
      "strengths": [
        "Largest Benjamin Franklin LoRA family proven trainable on this RTX 3070 8GB machine.",
        "Best base reasoning/coherence among the local Franklin adapters.",
        "Good short-turn continuity in the coherence benchmark."
      ],
      "weaknesses": [
        "Qwen2.5 7B base is already highly steerable, so improvements over the prompted base are modest.",
        "q/v-only LoRA is weak for implanting stubborn factual corrections.",
        "Craven Street/Hewson factuality remains unreliable unless retrieval/prompt context is supplied."
      ],
      "project_uses": [
        "Conversational Franklin persona in local apps.",
        "A strong baseline for RAG-backed historical character demos.",
        "Best starting point for further 7B experiments."
      ],
      "compute_requirements": "Inference: RTX 3070 8GB works in 4-bit with the adapter; expect roughly 6-7GB VRAM. Training proven only with q_proj/v_proj, r=4 or r=8, max_seq_length=512, batch_size=1, gradient_accumulation=16; full-module LoRA is not recommended on 8GB."
    },
    {
      "name": "qwen3-1.7b-ben-franklin-thinking-v2-lora",
      "adapter_dir": "adapters/qwen3-1.7b-ben-franklin-thinking-v2-lora",
      "size_bytes": 835640240,
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      "lora_r": 32,
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      "target_modules": [
        "q_proj",
        "v_proj",
        "down_proj",
        "k_proj",
        "gate_proj",
        "o_proj",
        "up_proj"
      ],
      "data_mix": [
        [
          "franklin_qwen3_8b_chatml_answer_clean.jsonl",
          2400
        ],
        [
          "franklin_7b_coherence_repair_v2.jsonl",
          287
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      ],
      "benchmark": null,
      "strengths": [
        "Largest Benjamin Franklin LoRA family proven trainable on this RTX 3070 8GB machine.",
        "Best base reasoning/coherence among the local Franklin adapters.",
        "Good short-turn continuity in the coherence benchmark."
      ],
      "weaknesses": [
        "Qwen2.5 7B base is already highly steerable, so improvements over the prompted base are modest.",
        "q/v-only LoRA is weak for implanting stubborn factual corrections.",
        "Craven Street/Hewson factuality remains unreliable unless retrieval/prompt context is supplied."
      ],
      "project_uses": [
        "Conversational Franklin persona in local apps.",
        "A strong baseline for RAG-backed historical character demos.",
        "Best starting point for further 7B experiments."
      ],
      "compute_requirements": "Inference: RTX 3070 8GB works in 4-bit with the adapter; expect roughly 6-7GB VRAM. Training proven only with q_proj/v_proj, r=4 or r=8, max_seq_length=512, batch_size=1, gradient_accumulation=16; full-module LoRA is not recommended on 8GB."
    },
    {
      "name": "qwen3-1.7b-ben-franklin-thinking-v3-negative-identity-lora",
      "adapter_dir": "adapters/qwen3-1.7b-ben-franklin-thinking-v3-negative-identity-lora",
      "size_bytes": 835668626,
      "size_gb": 0.78,
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        "q_proj",
        "v_proj",
        "k_proj",
        "up_proj",
        "down_proj",
        "o_proj",
        "gate_proj"
      ],
      "data_mix": [
        [
          "franklin_qwen3_8b_chatml_answer_clean.jsonl",
          2400
        ],
        [
          "franklin_7b_factual_coherence_repair_v3.jsonl",
          308
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      ],
      "benchmark": null,
      "strengths": [
        "Largest Benjamin Franklin LoRA family proven trainable on this RTX 3070 8GB machine.",
        "Best base reasoning/coherence among the local Franklin adapters.",
        "Good short-turn continuity in the coherence benchmark."
      ],
      "weaknesses": [
        "Qwen2.5 7B base is already highly steerable, so improvements over the prompted base are modest.",
        "q/v-only LoRA is weak for implanting stubborn factual corrections.",
        "Craven Street/Hewson factuality remains unreliable unless retrieval/prompt context is supplied."
      ],
      "project_uses": [
        "Conversational Franklin persona in local apps.",
        "A strong baseline for RAG-backed historical character demos.",
        "Best starting point for further 7B experiments."
      ],
      "compute_requirements": "Inference: RTX 3070 8GB works in 4-bit with the adapter; expect roughly 6-7GB VRAM. Training proven only with q_proj/v_proj, r=4 or r=8, max_seq_length=512, batch_size=1, gradient_accumulation=16; full-module LoRA is not recommended on 8GB."
    },
    {
      "name": "qwen3-1.7b-ben-franklin-thinking-v4-balanced-lora",
      "adapter_dir": "adapters/qwen3-1.7b-ben-franklin-thinking-v4-balanced-lora",
      "size_bytes": 835674029,
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      "data_mix": [
        [
          "franklin_qwen3_8b_chatml_answer_clean.jsonl",
          2400
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      "benchmark": null,
      "strengths": [
        "Largest Benjamin Franklin LoRA family proven trainable on this RTX 3070 8GB machine.",
        "Best base reasoning/coherence among the local Franklin adapters.",
        "Good short-turn continuity in the coherence benchmark."
      ],
      "weaknesses": [
        "Qwen2.5 7B base is already highly steerable, so improvements over the prompted base are modest.",
        "q/v-only LoRA is weak for implanting stubborn factual corrections.",
        "Craven Street/Hewson factuality remains unreliable unless retrieval/prompt context is supplied."
      ],
      "project_uses": [
        "Conversational Franklin persona in local apps.",
        "A strong baseline for RAG-backed historical character demos.",
        "Best starting point for further 7B experiments."
      ],
      "compute_requirements": "Inference: RTX 3070 8GB works in 4-bit with the adapter; expect roughly 6-7GB VRAM. Training proven only with q_proj/v_proj, r=4 or r=8, max_seq_length=512, batch_size=1, gradient_accumulation=16; full-module LoRA is not recommended on 8GB."
    },
    {
      "name": "qwen3-1.7b-ben-franklin-thinking-v5-ood-fixed-lora",
      "adapter_dir": "adapters/qwen3-1.7b-ben-franklin-thinking-v5-ood-fixed-lora",
      "size_bytes": 835640341,
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        "up_proj",
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      "data_mix": [
        [
          "franklin_qwen3_8b_chatml_answer_clean.jsonl",
          2400
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      "benchmark": null,
      "strengths": [
        "Largest Benjamin Franklin LoRA family proven trainable on this RTX 3070 8GB machine.",
        "Best base reasoning/coherence among the local Franklin adapters.",
        "Good short-turn continuity in the coherence benchmark."
      ],
      "weaknesses": [
        "Qwen2.5 7B base is already highly steerable, so improvements over the prompted base are modest.",
        "q/v-only LoRA is weak for implanting stubborn factual corrections.",
        "Craven Street/Hewson factuality remains unreliable unless retrieval/prompt context is supplied."
      ],
      "project_uses": [
        "Conversational Franklin persona in local apps.",
        "A strong baseline for RAG-backed historical character demos.",
        "Best starting point for further 7B experiments."
      ],
      "compute_requirements": "Inference: RTX 3070 8GB works in 4-bit with the adapter; expect roughly 6-7GB VRAM. Training proven only with q_proj/v_proj, r=4 or r=8, max_seq_length=512, batch_size=1, gradient_accumulation=16; full-module LoRA is not recommended on 8GB."
    },
    {
      "name": "qwen3-1.7b-ben-franklin-thinking-v6-1-ood-fixed-lora",
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        [
          "franklin_qwen3_8b_chatml_answer_clean.jsonl",
          2400
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      "strengths": [
        "Largest Benjamin Franklin LoRA family proven trainable on this RTX 3070 8GB machine.",
        "Best base reasoning/coherence among the local Franklin adapters.",
        "Good short-turn continuity in the coherence benchmark."
      ],
      "weaknesses": [
        "Qwen2.5 7B base is already highly steerable, so improvements over the prompted base are modest.",
        "q/v-only LoRA is weak for implanting stubborn factual corrections.",
        "Craven Street/Hewson factuality remains unreliable unless retrieval/prompt context is supplied."
      ],
      "project_uses": [
        "Conversational Franklin persona in local apps.",
        "A strong baseline for RAG-backed historical character demos.",
        "Best starting point for further 7B experiments."
      ],
      "compute_requirements": "Inference: RTX 3070 8GB works in 4-bit with the adapter; expect roughly 6-7GB VRAM. Training proven only with q_proj/v_proj, r=4 or r=8, max_seq_length=512, batch_size=1, gradient_accumulation=16; full-module LoRA is not recommended on 8GB."
    },
    {
      "name": "qwen3-1.7b-ben-franklin-thinking-v6-contrastive-lora",
      "adapter_dir": "adapters/qwen3-1.7b-ben-franklin-thinking-v6-contrastive-lora",
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        "Largest Benjamin Franklin LoRA family proven trainable on this RTX 3070 8GB machine.",
        "Best base reasoning/coherence among the local Franklin adapters.",
        "Good short-turn continuity in the coherence benchmark."
      ],
      "weaknesses": [
        "Qwen2.5 7B base is already highly steerable, so improvements over the prompted base are modest.",
        "q/v-only LoRA is weak for implanting stubborn factual corrections.",
        "Craven Street/Hewson factuality remains unreliable unless retrieval/prompt context is supplied."
      ],
      "project_uses": [
        "Conversational Franklin persona in local apps.",
        "A strong baseline for RAG-backed historical character demos.",
        "Best starting point for further 7B experiments."
      ],
      "compute_requirements": "Inference: RTX 3070 8GB works in 4-bit with the adapter; expect roughly 6-7GB VRAM. Training proven only with q_proj/v_proj, r=4 or r=8, max_seq_length=512, batch_size=1, gradient_accumulation=16; full-module LoRA is not recommended on 8GB."
    },
    {
      "name": "qwen3-1.7b-ben-franklin-thinking-v7-natural-dialogue-lora",
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      "data_mix": [
        [
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          2400
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      "benchmark": null,
      "strengths": [
        "Largest Benjamin Franklin LoRA family proven trainable on this RTX 3070 8GB machine.",
        "Best base reasoning/coherence among the local Franklin adapters.",
        "Good short-turn continuity in the coherence benchmark.",
        "Focused on more natural short conversational replies."
      ],
      "weaknesses": [
        "Qwen2.5 7B base is already highly steerable, so improvements over the prompted base are modest.",
        "q/v-only LoRA is weak for implanting stubborn factual corrections.",
        "Craven Street/Hewson factuality remains unreliable unless retrieval/prompt context is supplied."
      ],
      "project_uses": [
        "Conversational Franklin persona in local apps.",
        "A strong baseline for RAG-backed historical character demos.",
        "Best starting point for further 7B experiments."
      ],
      "compute_requirements": "Inference: RTX 3070 8GB works in 4-bit with the adapter; expect roughly 6-7GB VRAM. Training proven only with q_proj/v_proj, r=4 or r=8, max_seq_length=512, batch_size=1, gradient_accumulation=16; full-module LoRA is not recommended on 8GB."
    },
    {
      "name": "qwen3-1.7b-ben-franklin-thinking-v8-minimal-thought-lora",
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      "target_modules": [
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      "benchmark": null,
      "strengths": [
        "Largest Benjamin Franklin LoRA family proven trainable on this RTX 3070 8GB machine.",
        "Best base reasoning/coherence among the local Franklin adapters.",
        "Good short-turn continuity in the coherence benchmark.",
        "Focused on reducing visible thought/over-reasoning style."
      ],
      "weaknesses": [
        "Qwen2.5 7B base is already highly steerable, so improvements over the prompted base are modest.",
        "q/v-only LoRA is weak for implanting stubborn factual corrections.",
        "Craven Street/Hewson factuality remains unreliable unless retrieval/prompt context is supplied."
      ],
      "project_uses": [
        "Conversational Franklin persona in local apps.",
        "A strong baseline for RAG-backed historical character demos.",
        "Best starting point for further 7B experiments."
      ],
      "compute_requirements": "Inference: RTX 3070 8GB works in 4-bit with the adapter; expect roughly 6-7GB VRAM. Training proven only with q_proj/v_proj, r=4 or r=8, max_seq_length=512, batch_size=1, gradient_accumulation=16; full-module LoRA is not recommended on 8GB."
    },
    {
      "name": "qwen3-1.7b-ben-franklin-thinking-v9-factual-dialogue-lora",
      "adapter_dir": "adapters/qwen3-1.7b-ben-franklin-thinking-v9-factual-dialogue-lora",
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      "target_modules": [
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        "down_proj",
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      ],
      "data_mix": [
        [
          "franklin_qwen3_8b_chatml_answer_clean.jsonl",
          2400
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        [
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      "strengths": [
        "Largest Benjamin Franklin LoRA family proven trainable on this RTX 3070 8GB machine.",
        "Best base reasoning/coherence among the local Franklin adapters.",
        "Good short-turn continuity in the coherence benchmark.",
        "Focused on factual dialogue and hard Franklin biography prompts."
      ],
      "weaknesses": [
        "Qwen2.5 7B base is already highly steerable, so improvements over the prompted base are modest.",
        "q/v-only LoRA is weak for implanting stubborn factual corrections.",
        "Craven Street/Hewson factuality remains unreliable unless retrieval/prompt context is supplied."
      ],
      "project_uses": [
        "Conversational Franklin persona in local apps.",
        "A strong baseline for RAG-backed historical character demos.",
        "Best starting point for further 7B experiments."
      ],
      "compute_requirements": "Inference: RTX 3070 8GB works in 4-bit with the adapter; expect roughly 6-7GB VRAM. Training proven only with q_proj/v_proj, r=4 or r=8, max_seq_length=512, batch_size=1, gradient_accumulation=16; full-module LoRA is not recommended on 8GB."
    },
    {
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      "adapter_dir": "adapters/qwen3-1.7b-ben-franklin-thinking-v9-from-v2-factual-dialogue-lora",
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        "q_proj",
        "k_proj",
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      "data_mix": [
        [
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          2400
        ],
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        [
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      "strengths": [
        "Largest Benjamin Franklin LoRA family proven trainable on this RTX 3070 8GB machine.",
        "Best base reasoning/coherence among the local Franklin adapters.",
        "Good short-turn continuity in the coherence benchmark.",
        "Focused on factual dialogue and hard Franklin biography prompts."
      ],
      "weaknesses": [
        "Qwen2.5 7B base is already highly steerable, so improvements over the prompted base are modest.",
        "q/v-only LoRA is weak for implanting stubborn factual corrections.",
        "Craven Street/Hewson factuality remains unreliable unless retrieval/prompt context is supplied."
      ],
      "project_uses": [
        "Conversational Franklin persona in local apps.",
        "A strong baseline for RAG-backed historical character demos.",
        "Best starting point for further 7B experiments."
      ],
      "compute_requirements": "Inference: RTX 3070 8GB works in 4-bit with the adapter; expect roughly 6-7GB VRAM. Training proven only with q_proj/v_proj, r=4 or r=8, max_seq_length=512, batch_size=1, gradient_accumulation=16; full-module LoRA is not recommended on 8GB."
    }
  ]
}