Run Status

• Status: complete_skipped
• Adapter present: True
• Latest checkpoint: outputs/qwen-capability-light/stage1-behavior-seed-sft/checkpoint-80
• Best checkpoint: outputs/qwen-capability-light/stage1-behavior-seed-sft/checkpoint-80
• Best eval loss: 2.720693588256836
• Trainer state: outputs/qwen-capability-light/stage1-behavior-seed-sft/trainer_state.json
• Global step: 80
• First Loss: 1.0619739294052124
• Final Loss: 1.046101450920105
• Min Loss: 0.5612894296646118
• Max Loss: 1.6812756061553955
• Loss Points: 80
• First Eval Loss: 2.7349205017089844
• Final Eval Loss: 2.720693588256836
• Min Eval Loss: 2.720693588256836
• Max Eval Loss: 2.7349205017089844
• Eval Loss Points: 5
• Best Eval Loss: 2.720693588256836
• Best Global Step: 80
• Train Runtime S: 1337.8865

Generated files:

• training_config.json
• stage_report.json
• loss_history.csv
• loss_curve.svg
• eval_loss_history.csv
• eval_loss_curve.svg

Context

• Purpose: Light behavior seed: enough trace format/tool habits without drilling a full behavior path.
• Previous adapter: none; stage 1 initializes the LoRA
• Next stage: stage2-capability-step-sft
• Base model: Qwen/Qwen3.5-2B
• Data file: data/assembled/sft_qwen_messages_behavior_seed_light.jsonl
• Eval file: data/eval/eval_sft_with_retention.jsonl
• LoRA r/alpha/dropout: 16 / 16 / 0.0
• Learning rate: 8e-07
• Epochs: 1.0
• Merged 16-bit model: not configured for this stage

Upstream Data

• armand0e/qwen3.7-max-pi-traces
• armand0e/badlogicgames-pi-mono-opus-filtered
• armand0e/gpt-5.5-agent
• armand0e/gpt-5.5-chat
• TeichAI/claude-4.5-opus-high-reasoning-250x
• TeichAI/Claude-Opus-4.6-Reasoning-887x

Compact Local Sample

json
Copy code
{
  "messages": [
    {
      "content": "You are a helpful assistant in chat mode. When the user asks for code or an artifact, return the artifact or a concrete patch in the message. Do not say you will edit files unless a file-editing tool is actually available.",
      "role": "system"
    },
    {
      "content": "No file tools are available here. Fix this snippet and return the corrected code block only, plus one short note:\n'''python\ndef normalize_tags(tags):\n    return [t.lower() for t in tags.split(',')]\n'''",
      "role": "user"
    },
    {
      "content": "'''python\ndef normalize_tags(tags):\n    if not tags:\n        return []\n    return [part.strip().lower() for part in tags.split(',') if part.strip()]\n'''\n\nNote: The function now handles None, trims whitespace, and drops empty tags.",
      "reasoning_content": "The user wants a corrected snippet, but no edit tool is available. Provide the code directly and avoid claiming a file was changed.",
      "role": "assistant"
    }
  ],
  "metadata": {
    "failure_type": "claims_edit_without_tool",
    "family": "no_tool_code_edit",
    "has_system": true,
    "source": "chat_repair_pack",
    "source_key": "chat
...[truncated]

Reproduction

The exact stage command and package versions are in training_config.json.