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metadata
license: mit
tags:
  - algo-sft-eval-redo
  - long_arithmetic
  - algo

algo-sft-eval-traces-long-arithmetic-chunked-v4

Full eval traces for algo-sft-long-arithmetic-chunked 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-long-arithmetic-chunked",
  "description": "Full eval traces for algo-sft-long-arithmetic-chunked 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-long-arithmetic-chunked-v4", split="train")
print(f"Loaded {len(dataset)} rows")

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