こんにちは
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1 changed files with 19 additions and 19 deletions
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@ -22,7 +22,7 @@ deepspeed:
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reduce_scatter: true
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reduce_bucket_size: 500000000
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contiguous_gradients: true
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cpu_offload: false # Keep on GPU for speed with small model
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cpu_offload: true # Enable CPU offload for memory efficiency
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optimizer:
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type: "AdamW"
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@ -47,23 +47,23 @@ deepspeed:
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gradient_clipping: 1.0
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train_batch_size: 512 # Total batch size across all GPUs
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train_micro_batch_size_per_gpu: 64 # Per-GPU batch size
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train_batch_size: 64 # Total batch size across all GPUs
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train_micro_batch_size_per_gpu: 8 # Per-GPU batch size
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progressive_stages:
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- name: "basic_cot"
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description: "Basic Chain-of-Thought reasoning"
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dataset_path: "./data/basic_cot/"
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adapter_config:
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r: 32 # Larger rank with 8 GPUs
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lora_alpha: 64
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r: 16 # Reduced rank for memory
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lora_alpha: 32
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lora_dropout: 0.1
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target_modules: ["q_proj", "k_proj", "v_proj", "o_proj"]
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init_lora_weights: true
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training:
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num_epochs: 2
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per_device_batch_size: 64 # Large batch with DeepSpeed
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gradient_accumulation_steps: 1 # No accumulation needed
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per_device_batch_size: 8 # Reduced for memory
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gradient_accumulation_steps: 1
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learning_rate: 5e-4
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warmup_steps: 100
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max_length: 1024
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@ -72,23 +72,23 @@ progressive_stages:
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weight_decay: 0.001
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save_steps: 50
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logging_steps: 10
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dataloader_num_workers: 8
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dataloader_pin_memory: true
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dataloader_num_workers: 4
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dataloader_pin_memory: false
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- name: "math_reasoning"
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description: "Mathematical reasoning with OpenR1-Math-220k dataset"
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dataset_path: "open-r1/OpenR1-Math-220k"
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inherit_from: "basic_cot"
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adapter_config:
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r: 64 # Larger rank for math reasoning
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lora_alpha: 128
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r: 32 # Reduced rank for memory
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lora_alpha: 64
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lora_dropout: 0.1
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target_modules: ["q_proj", "k_proj", "v_proj", "o_proj", "gate_proj", "up_proj", "down_proj"]
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init_lora_weights: true
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training:
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num_epochs: 1
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per_device_batch_size: 32 # Reduce for longer sequences
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gradient_accumulation_steps: 1
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per_device_batch_size: 4 # Further reduce for longer sequences
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gradient_accumulation_steps: 2
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learning_rate: 3e-4
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warmup_steps: 200
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max_length: 2048
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@ -97,7 +97,7 @@ progressive_stages:
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weight_decay: 0.001
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save_steps: 100
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logging_steps: 20
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dataloader_num_workers: 8
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dataloader_num_workers: 4
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dataset_config:
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streaming: true
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max_samples: 500000 # Process more data with 8 GPUs
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@ -108,15 +108,15 @@ progressive_stages:
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dataset_path: "open-r1/Mixture-of-Thoughts"
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inherit_from: "math_reasoning"
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adapter_config:
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r: 128 # Maximum rank for complex reasoning
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lora_alpha: 256
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r: 64 # Reduced rank for memory
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lora_alpha: 128
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lora_dropout: 0.1
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target_modules: ["q_proj", "k_proj", "v_proj", "o_proj", "gate_proj", "up_proj", "down_proj"]
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init_lora_weights: true
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training:
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num_epochs: 1
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per_device_batch_size: 16 # Reduce for very long sequences
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gradient_accumulation_steps: 2
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per_device_batch_size: 2 # Very small for long sequences
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gradient_accumulation_steps: 4
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learning_rate: 2e-4
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warmup_steps: 300
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max_length: 4096
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@ -125,7 +125,7 @@ progressive_stages:
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weight_decay: 0.001
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save_steps: 200
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logging_steps: 50
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dataloader_num_workers: 8
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dataloader_num_workers: 4
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dataset_config:
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streaming: true
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max_samples: 800000 # Process even more data
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