algo-sft-eval-traces-conlang-morphology-distill-qwq-v4

Full eval traces for algo-sft-conlang-morphology-distill-qwq across test/harder/ood splits

Dataset Info

• Rows: 2000
• Columns: 11

Columns

Column	Type	Description
question_id	Value('string')	Unique question identifier from eval set
split	Value('string')	Evaluation split: test (in-distribution), harder (scaled up), ood (structural out-of-distribution)
domain	Value('string')	Task domain: formal_logic, conlang_morphology, cellular_automata, long_arithmetic
task	Value('string')	Specific task variant (e.g., formal_logic_bottom_up)
prompt	Value('string')	Full prompt sent to the model
model_response	Value('string')	Complete untruncated model output
extracted_answer	Value('string')	Answer extracted by domain-specific parser
ground_truth	Value('string')	Expected correct answer
correct	Value('bool')	Whether extracted_answer matched ground_truth
finish_reason	Value('string')	vLLM finish reason: stop (natural end) or length (hit max_tokens)
token_count	Value('int64')	Number of tokens in model_response

Generation Parameters

{
  "script_name": "eval_model.py",
  "model": "reasoning-degeneration-dev/algo-sft-conlang-morphology-distill-qwq",
  "description": "Full eval traces for algo-sft-conlang-morphology-distill-qwq across test/harder/ood splits",
  "hyperparameters": {
    "max_tokens": 32768,
    "max_model_len": 32768,
    "temperature": 0.0,
    "base_model": "Qwen/Qwen2.5-1.5B-Instruct"
  },
  "input_datasets": []
}

Usage

from datasets import load_dataset

dataset = load_dataset("raca-workspace-v1/algo-sft-eval-traces-conlang-morphology-distill-qwq-v4", split="train")
print(f"Loaded {len(dataset)} rows")

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