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31dc8dc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | experiment:
project: "your_project" # Output directory for evaluation results
rollout:
tensor_parallel_size: 1 # set to 1 by default, if oom, try reduce max_active first, if still oom, set tensor_parallel_size to 8
max_active: 256
num_task_per_step: 1
num_response_per_task: 1
temperature: 0.1
max_token: 2000
block_size: 4
denoising_steps_per_block: 4
top_p: 1.0
top_k: 0
remasking_strategy: "low_confidence_static" #"low_confidence_static""low_confidence_dynamic"
dynamic_threshold: 0.9 # no use for "low_confidence_static"
start_with_think: False
random_init_ratio: 0.0
# Batch processing: split dataset into batches to avoid KV cache exhaustion
# If None or 0, process all prompts at once (original behavior)
# If set to a positive number, process prompts in batches of this size
batch_size: 50 # e.g., set to 50 to process 50 prompts at a time in case we run out of KV cache space
evaluation:
# Model checkpoint to evaluate (overrides 'model' above if specified)
checkpoint_path: "/path/to/your/checkpoint"
# Dataset configuration
# eval_dataset: "MATH_train" # Dataset name (must exist in data/{eval_dataset}.json)
eval_dataset: "your_dataset"
data_type: "math" # Task type: "math", "code", or "option"
# Distributed evaluation (for multi-node setups)
num_node: 1 # Total number of nodes
node_index: 0 # Current node index (0-indexed)
# Output options
output_unmasking_history: true # Save step-by-step unmasking history
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