Instructions to use yocoms/system1-qlora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use yocoms/system1-qlora with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Upload 06b_bf16_r16/train_args.json with huggingface_hub
Browse files- 06b_bf16_r16/train_args.json +32 -0
06b_bf16_r16/train_args.json
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{
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"base": "Qwen/Qwen3-0.6B",
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"corpus": "data/distill/train_structured.jsonl",
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"out": "results/loop9h/p3_m1",
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"precision": "bf16",
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"mode": "lora",
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"lora_r": 16,
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"targets": "dense",
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"max_len": 1024,
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"batch": 8,
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"grad_accum": 3,
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"max_steps": 2000,
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"lr": 0.0002,
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"warmup": 30,
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"min_lr_frac": 0.1,
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"weight_decay": 0.0,
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"permute_prob": 0.5,
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"kd_alpha": 1.0,
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"kd_temp": 2.0,
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"no_grad_checkpoint": false,
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"vram_cap_gb": 8.0,
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"save_steps": 250,
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"seed": 0,
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"limit_rows": 0,
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"deadline": 1790185384.0,
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"trainable_params": 10092544,
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"steps_done": 2000,
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"steps_this_run": 2000,
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"wall_s": 4478.817822694778,
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"sps_steady": 2.2359451534156514,
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"hit_deadline": false
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}
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