{
  "config": {
    "model_X": "Qwen/Qwen2.5-3B-Instruct",
    "model_Y": "meta-llama/Llama-3.2-3B-Instruct",
    "hub_repo": "CK0607/cross-model-lora-prediction-3b",
    "lora": {
      "r": 16,
      "alpha": 32,
      "targets": [
        "q_proj",
        "k_proj",
        "v_proj",
        "o_proj",
        "gate_proj",
        "up_proj",
        "down_proj"
      ],
      "dropout": 0.0
    },
    "train": {
      "examples": 1500,
      "eval_examples": 300,
      "round5_eval_examples": 100,
      "round5_fast_surrogate": true,
      "epochs": 3.0,
      "bs": 8,
      "lr": 0.0002,
      "max_len": 512
    },
    "r4_anchor_names": [
      "gsm8k",
      "mbpp",
      "sciq",
      "arc_easy",
      "openbookqa",
      "svamp",
      "multiarith",
      "mmlu_high_school_biology",
      "math_counting_easy",
      "humaneval",
      "mmlu_high_school_physics",
      "mbpp_sanitized",
      "mmlu_elementary_math",
      "math_algebra_easy",
      "aqua_rat",
      "medmcqa_easy"
    ],
    "r5_requested_new_anchors": [
      "aqua_rat_numeric",
      "math_counting_easy",
      "mawps",
      "mbpp_sanitized",
      "humaneval",
      "conala_curated",
      "medmcqa_easy",
      "pubmedqa_pqal"
    ],
    "r5_new_anchor_names": [
      "aqua_rat_numeric",
      "math_counting_easy",
      "mawps",
      "mbpp_sanitized",
      "humaneval",
      "conala_curated",
      "medmcqa_easy",
      "pubmedqa_pqal"
    ],
    "dropped": [],
    "pool_anchor_names": [
      "r4:gsm8k",
      "r4:mbpp",
      "r4:sciq",
      "r4:arc_easy",
      "r4:openbookqa",
      "r4:svamp",
      "r4:multiarith",
      "r4:mmlu_high_school_biology",
      "r4:math_counting_easy",
      "r4:humaneval",
      "r4:mmlu_high_school_physics",
      "r4:mbpp_sanitized",
      "r4:mmlu_elementary_math",
      "r4:math_algebra_easy",
      "r4:aqua_rat",
      "r4:medmcqa_easy",
      "r5:aqua_rat_numeric",
      "r5:math_counting_easy",
      "r5:mawps",
      "r5:mbpp_sanitized",
      "r5:humaneval",
      "r5:conala_curated",
      "r5:medmcqa_easy",
      "r5:pubmedqa_pqal"
    ],
    "heldouts": [
      "gsm_hard",
      "gsm8k_test_500",
      "mbpp_test_held",
      "mbpp_plus",
      "openbookqa_test"
    ],
    "N_values": [
      4,
      8,
      12,
      16,
      24
    ],
    "methods": [
      "mean",
      "global_ridge",
      "topk8_global_ridge"
    ],
    "seeds": [
      11,
      22,
      33,
      44,
      55
    ]
  },
  "dataset_audit": {
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        "kind": "math_num",
        "dataset": "deepmind/aqua_rat",
        "config": "raw",
        "train_rows_sampled": 20,
        "eval_rows_sampled": 10,
        "labels": [],
        "sample": {
          "messages": [
            {
              "role": "user",
              "content": "Solve the math problem. Respond with only the final answer.\n\nProblem: From (1, 2, 3, 4, 5, 6), one number is picked out and replaced and one number is picked out again. If the sum of the 2 numbers is 9, what is the probability that the 2 numbers included the number 5?\n\nFinal answer:"
            },
            {
              "role": "assistant",
              "content": "1/2"
            }
          ]
        },
        "ok": true
      },
      "math_counting_easy": {
        "domain": "math",
        "kind": "math_solution",
        "dataset": "EleutherAI/hendrycks_math",
        "config": "counting_and_probability",
        "train_rows_sampled": 20,
        "eval_rows_sampled": 10,
        "labels": [],
        "sample": {
          "messages": [
            {
              "role": "user",
              "content": "Solve the math problem. Respond with only the final answer.\n\nProblem: Alex has 10 different kinds of lunch meat and 9 different kinds of cheese. If he wants to make a sandwich with one kind of meat and two kinds of cheese, how many different sandwiches could he make?  (It does not matter in which order he chooses the two types of cheese.)\n\nFinal answer:"
            },
            {
              "role": "assistant",
              "content": "360"
            }
          ]
        },
        "ok": true
      },
      "mawps": {
        "domain": "math",
        "kind": "math_num",
        "dataset": "MU-NLPC/Calc-mawps",
        "config": null,
        "train_rows_sampled": 20,
        "eval_rows_sampled": 10,
        "labels": [],
        "sample": {
          "messages": [
            {
              "role": "user",
              "content": "Solve the math problem. Respond with only the final answer.\n\nProblem: Marilyn had 279 Beg. Daryl clasped some Beg. Now Marilyn has 59  Beg. How many did Daryl claspeds?\n\nFinal answer:"
            },
            {
              "role": "assistant",
              "content": "220"
            }
          ]
        },
        "ok": true
      },
      "mbpp_sanitized": {
        "domain": "code",
        "kind": "code",
        "dataset": "google-research-datasets/mbpp",
        "config": "sanitized",
        "train_rows_sampled": 20,
        "eval_rows_sampled": 10,
        "labels": [],
        "sample": {
          "messages": [
            {
              "role": "user",
              "content": "Write a Python function that solves the task. Respond with only code.\n\nTask: Write a function to reverse words seperated by spaces in a given string.\n\nTests:\nassert reverse_words(\"python program\")==(\"program python\")\nassert reverse_words(\"java language\")==(\"language java\")\nassert reverse_words(\"indian man\")==(\"man indian\")\n\nCode:"
            },
            {
              "role": "assistant",
              "content": "def reverse_words(s):\n        return ' '.join(reversed(s.split()))"
            }
          ]
        },
        "ok": true
      },
      "humaneval": {
        "domain": "code",
        "kind": "code",
        "dataset": "openai/openai_humaneval",
        "config": null,
        "train_rows_sampled": 20,
        "eval_rows_sampled": 10,
        "labels": [],
        "sample": {
          "messages": [
            {
              "role": "user",
              "content": "Complete the following Python function. Respond with only the completion code.\n\ndef below_threshold(l: list, t: int):\n    \"\"\"Return True if all numbers in the list l are below threshold t.\n    >>> below_threshold([1, 2, 4, 10], 100)\n    True\n    >>> below_threshold([1, 20, 4, 10], 5)\n    False\n    \"\"\""
            },
            {
              "role": "assistant",
              "content": "for e in l:\n        if e >= t:\n            return False\n    return True"
            }
          ]
        },
        "ok": true
      },
      "conala_curated": {
        "domain": "code",
        "kind": "code",
        "dataset": "codeparrot/conala-mined-curated",
        "config": null,
        "train_rows_sampled": 20,
        "eval_rows_sampled": 10,
        "labels": [],
        "sample": {
          "messages": [
            {
              "role": "user",
              "content": "Write a Python code snippet for this intent. Respond with only code.\n\nIntent: print all contacts in class all_contacts\n\nCode:"
            },
            {
              "role": "assistant",
              "content": "all_contacts = []"
            }
          ]
        },
        "ok": true
      },
      "medmcqa_easy": {
        "domain": "science",
        "kind": "mcq",
        "dataset": "openlifescienceai/medmcqa",
        "config": null,
        "train_rows_sampled": 20,
        "eval_rows_sampled": 10,
        "labels": [
          "A",
          "B",
          "C",
          "D",
          "E",
          "F",
          "G",
          "H"
        ],
        "sample": {
          "messages": [
            {
              "role": "user",
              "content": "Answer the multiple-choice question. Respond with only the option letter.\n\nApolipoprotein A-I (Apo A-I) is found in which of the following lipid components?\nA. LDL\nB. HDL\nC. VLDL\nD. Chylomicron\nAnswer:"
            },
            {
              "role": "assistant",
              "content": "B"
            }
          ]
        },
        "ok": true
      },
      "pubmedqa_pqal": {
        "domain": "science",
        "kind": "short",
        "dataset": "qiaojin/PubMedQA",
        "config": "pqa_labeled",
        "train_rows_sampled": 20,
        "eval_rows_sampled": 10,
        "labels": [
          "yes",
          "no",
          "maybe"
        ],
        "sample": {
          "messages": [
            {
              "role": "user",
              "content": "Answer the biomedical question with only one of: yes, no, maybe.\n\nContext: To assess whether eligibility to an adjuvant chemotherapy protocol in itself represents a good prognostic factor after radical cystectomy for bladder cancer. Between April 1984 and May 1989, our institution entered 35 patients with invasive bladder cancer into the Swiss Group for Clinical and Epidemiological Cancer Research (SAKK) study 09/84. They were randomly assigned to either observation or three postoperative courses of cisplatin monotherapy after cystectomy. This study had a negative result. The outcome of these 35 patients (protocol group) was compared with an age- and tumor-stage-matched cohort (matched group; n = 35) who also underwent cystectomy during the same period, but were not entered into the SAKK study, as well as the remaining 57 patients treated during the study period for the same indication (remaining group). Median overall survival decreased from 76.3 months in the protocol group to 52.1 months in the matched group and to 20.3 months in the remaining group. The respective times of median recurrence-free survival were 67.2, 16.0, and 9.4 months. Tumor progression occurred in 46% of the protocol group compared with 69% in the matched group and 65% in the remaining group (P<.05). Cancer-related death was noted in 40% of the protocol group, 57% in the matched group, and 56% in the remaining group.\n\nQuestion: Is eligibility for a chemotherapy protocol a good prognostic factor for invasive bladder cancer after radical cystectomy?\n\nAnswer:"
            },
            {
              "role": "assistant",
              "content": "yes"
            }
          ]
        },
        "ok": true
      }
    },
    "dropped": [],
    "kept": [
      "aqua_rat_numeric",
      "math_counting_easy",
      "mawps",
      "mbpp_sanitized",
      "humaneval",
      "conala_curated",
      "medmcqa_easy",
      "pubmedqa_pqal"
    ],
    "anchor_domain_counts": {
      "math": 3,
      "code": 3,
      "science": 2
    }
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  "training": [
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      "side": "X",
      "model": "Qwen/Qwen2.5-3B-Instruct",
      "task": "aqua_rat_numeric",
      "ok": true,
      "gpu": 0
    },
    {
      "side": "X",
      "model": "Qwen/Qwen2.5-3B-Instruct",
      "task": "humaneval",
      "ok": true,
      "gpu": 0
    },
    {
      "side": "Y",
      "model": "meta-llama/Llama-3.2-3B-Instruct",
      "task": "aqua_rat_numeric",
      "ok": true,
      "gpu": 1
    },
    {
      "side": "Y",
      "model": "meta-llama/Llama-3.2-3B-Instruct",
      "task": "humaneval",
      "ok": true,
      "gpu": 1
    },
    {
      "side": "X",
      "model": "Qwen/Qwen2.5-3B-Instruct",
      "task": "math_counting_easy",
      "ok": true,
      "gpu": 2
    },
    {
      "side": "X",
      "model": "Qwen/Qwen2.5-3B-Instruct",
      "task": "conala_curated",
      "ok": true,
      "gpu": 2
    },
    {
      "side": "Y",
      "model": "meta-llama/Llama-3.2-3B-Instruct",
      "task": "math_counting_easy",
      "ok": true,
      "gpu": 3
    },
    {
      "side": "Y",
      "model": "meta-llama/Llama-3.2-3B-Instruct",
      "task": "conala_curated",
      "ok": true,
      "gpu": 3
    },
    {
      "side": "X",
      "model": "Qwen/Qwen2.5-3B-Instruct",
      "task": "mawps",
      "ok": true,
      "gpu": 4
    },
    {
      "side": "X",
      "model": "Qwen/Qwen2.5-3B-Instruct",
      "task": "medmcqa_easy",
      "ok": true,
      "gpu": 4
    },
    {
      "side": "Y",
      "model": "meta-llama/Llama-3.2-3B-Instruct",
      "task": "mawps",
      "ok": true,
      "gpu": 5
    },
    {
      "side": "Y",
      "model": "meta-llama/Llama-3.2-3B-Instruct",
      "task": "medmcqa_easy",
      "ok": true,
      "gpu": 5
    },
    {
      "side": "X",
      "model": "Qwen/Qwen2.5-3B-Instruct",
      "task": "mbpp_sanitized",
      "ok": true,
      "gpu": 6
    },
    {
      "side": "X",
      "model": "Qwen/Qwen2.5-3B-Instruct",
      "task": "pubmedqa_pqal",
      "ok": true,
      "gpu": 6
    },
    {
      "side": "Y",
      "model": "meta-llama/Llama-3.2-3B-Instruct",
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      "gpu": 7
    },
    {
      "side": "Y",
      "model": "meta-llama/Llama-3.2-3B-Instruct",
      "task": "pubmedqa_pqal",
      "ok": true,
      "gpu": 7
    }
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  "baselines": {
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      "oracle": 0.15
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    "gsm8k_test_500": {
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    "mbpp_test_held": {
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      "oracle": 0.32
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    "mbpp_plus": {
      "base_Y": 0.21666666666666667,
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    "openbookqa_test": {
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      "anchors": [
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      "seed": 11,
      "method": "mean",
      "anchors": [
        "r4:multiarith",
        "r4:mbpp_sanitized",
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      "method": "global_ridge",
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        "r4:mbpp_sanitized",
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        "r5:medmcqa_easy"
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      "method": "topk8_global_ridge",
      "anchors": [
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        "r4:mbpp_sanitized",
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        "r5:medmcqa_easy"
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      "N": 4,
      "seed": 11,
      "method": "mean",
      "anchors": [
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        "r4:mbpp_sanitized",
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      "method": "global_ridge",
      "anchors": [
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        "r4:mbpp_sanitized",
        "r5:aqua_rat_numeric",
        "r5:medmcqa_easy"
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      "seed": 11,
      "method": "topk8_global_ridge",
      "anchors": [
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        "r4:mbpp_sanitized",
        "r5:aqua_rat_numeric",
        "r5:medmcqa_easy"
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      "selected_topk": [
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        "r4:multiarith",
        "r5:medmcqa_easy"
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      "seed": 22,
      "method": "mean",
      "anchors": [
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