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# ------------------------------------------------Environment Settings------------------------------------------------#
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# Directory paths for data and outputs
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data_dir: "/mnt/nas/thinhlpg/code/DeepSearch/data/flashrag_datasets/"
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save_dir: "/mnt/nas/thinhlpg/code/DeepSearch/logs"
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# Seed for reproducibility
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seed: 2024
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# Whether save intermediate data
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save_intermediate_data: True
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save_note: 'experiment'
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# -------------------------------------------------Retrieval Settings------------------------------------------------#
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# If set the remote url, the retriever will be a remote retriever and ignore following settings
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use_remote_retriever: True
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remote_retriever_url: "localhost:8001"
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instruction: ~ # instruction for retrieval model
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retrieval_topk: 5 # number of retrieved documents
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retrieval_batch_size: 256 # batch size for retrieval
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retrieval_use_fp16: True # whether to use fp16 for retrieval model
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retrieval_query_max_length: 128 # max length of the query
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save_retrieval_cache: False # whether to save the retrieval cache
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use_retrieval_cache: False # whether to use the retrieval cache
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retrieval_cache_path: ~ # path to the retrieval cache
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retrieval_pooling_method: ~ # set automatically if not provided
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# -------------------------------------------------Generator Settings------------------------------------------------#
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framework: sgl_remote # inference frame work of LLM, supporting: 'hf','vllm','fschat'
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sgl_remote_url: "localhost:8002"
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generator_model: "janhq/250404-llama-3.2-3b-instruct-grpo-03-s250" # name or path of the generator model, for laoding tokenizer
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generator_max_input_len: 2048 # max length of the input
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generation_params:
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do_sample: False
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max_tokens: 8192
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# -------------------------------------------------Evaluation Settings------------------------------------------------#
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# Metrics to evaluate the result
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metrics: [ 'em','f1','acc','precision','recall']
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# Specify setting for metric, will be called within certain metrics
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metric_setting:
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retrieval_recall_topk: 5
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save_metric_score: True # whether to save the metric score into txt file
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