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68 lines
1.2 KiB
YAML
68 lines
1.2 KiB
YAML
# check ./tina/utils/constant.py
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model_post_train_dataset_name: curated_rg_math
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model_post_train_type: grpo
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rl_post_train_reward_funcs:
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- tag_count_reward
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- length
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- accuracy
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rl_post_train_reward_weights:
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- 1.0
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- 1.0
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- 1.0
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# Model configs from trl
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model_name_or_path: Qwen2.5-3B-Instruct
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attn_implementation: flash_attention_2
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use_peft: false # full fine tune
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lora_r: 32
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lora_alpha: 128
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lora_dropout: 0.05
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lora_target_modules:
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- q_proj
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- k_proj
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- v_proj
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- o_proj
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- down_proj
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- up_proj
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- gate_proj
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# GRPO trainer configs from trl
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bf16: true
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use_vllm: true
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vllm_device: cuda:2
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vllm_gpu_memory_utilization: 0.9
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gradient_accumulation_steps: 1
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gradient_checkpointing: true
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gradient_checkpointing_kwargs:
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use_reentrant: false
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log_level: info
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logging_first_step: true
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logging_steps: 1
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logging_strategy: steps
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push_to_hub: true
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hub_strategy: every_save
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hub_private_repo: true
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hub_model_id: starzmustdie
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learning_rate: 1e-06
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lr_scheduler_type: constant_with_warmup
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lr_scheduler_kwargs:
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num_warmup_steps: 60
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max_prompt_length: 512
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max_completion_length: 2048
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max_steps: 600
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num_generations: 8
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num_train_epochs: 1
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overwrite_output_dir: true
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per_device_train_batch_size: 8
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report_to:
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- wandb
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save_strategy: steps
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save_steps: 200
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save_total_limit: 100
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seed: 42
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temperature: 0.6
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