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70 lines
1.3 KiB
Python
Executable file
70 lines
1.3 KiB
Python
Executable file
# Automatic Generated Configs
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# Model Related Settings
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actor="actor_model_path"
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reference="actor_model_path"
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chat_template="r1"
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dtype="auto"
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selective_recompute=1.0
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cpu_offload=False
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cuda_graph=True
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tp_size=4
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sp_size=1
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# Dataset Related Settings
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datasets="your dataset path"
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data_difficulty_balance_cfg=None
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num_workers=0
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# Generate Related Settings
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gen_global_batch=128
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gen_max_new=8192
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gen_max_length=10240
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gen_top_k=0
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gen_top_p=0.9
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temperature=1
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gen_do_sample=True
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max_prefill_batch=8
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prompt_repeat_k=4
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# Optimizer Related Settings
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rl_global_batch=128
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rl_micro_batch=4
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rl_mini_batch_steps=1
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warmup_steps=0
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actor_lr=1e-6
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actor_min_lr=1e-6
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wd=0.01
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max_grad_norm=1
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# General Settings
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work_dir="examples/xpuyu_usage/ckpts/experiment_name"
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checkpoint_interval=40
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log_interval=1
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seed=0
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debug=True
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# Reward Settings
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reward_shaping_type="grpo"
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loss_type="per_token"
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kl_coef=0.01
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stop_word="<｜end▁of▁sentence｜>"
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judgers_config = dict(
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bootcamp_judger=dict(
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stop_word=stop_word,
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num_processes=8,
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concurrency_per_proc=(8, 8),
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),
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)
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import json
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data_judger_mapping = {}
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with open("dataset_path", "r") as f:
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for line in f:
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item = json.loads(line)
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data_judger_mapping[item["metadata"]["data_source"]] = ["bootcamp_judger"]
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