43 lines
1.1 KiB
Markdown
43 lines
1.1 KiB
Markdown
---
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base_model: Qwen/Qwen2.5-7B-Instruct
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datasets:
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- Yano/exp-0223-027-realobs-llmagent-alfworld-data
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language:
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- en
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license: apache-2.0
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- qlora
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- lora
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- merged
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- alfworld
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- agent
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- realobs-llmagent
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---
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# exp-0223-027-realobs-llmagent-qwen2.5-7b
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Fine-tuned from **Qwen/Qwen2.5-7B-Instruct** using **QLoRA (4-bit, Unsloth)**.
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## Purpose
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ALFWorld SFT combining real environment observations from experiment 016
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with LLM-renarrated agent responses (strategic THOUGHTs + ACTION-dominant format).
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## Key Design
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- Environment responses (user): Real data from 016 (byte-exact preservation)
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- Agent responses (assistant): LLM-renarrated (strategic THOUGHT, not template)
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- Format: First turn THOUGHT+ACTION, subsequent ACTION-only, recovery THOUGHT after failures
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- Failure patterns: Naturally inherited from 016's 72% failure-containing trajectories
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## Training Configuration
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- Base model: Qwen/Qwen2.5-7B-Instruct
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- Method: QLoRA (4-bit), merged to 16-bit
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- Max sequence length: 2048
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- Epochs: 3
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- Learning rate: 2e-05
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- LoRA: r=64, alpha=128
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- Collator: AllAssistantTurnsCollator (all turns supervised)
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