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Answer the following problem. Explain your reasoning step by step. When you are finished, give your answer in this format: <answer>(your answer)</answer>.
# Problem
Using the numbers in the list [96, 97, 68], create an equation that equals 125. You can use basic arithmetic operations (+, -, *, /) and each number can o... | 97 + 96 - 68 | countdown_3arg | countdown | [
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Answer the following problem. Explain your reasoning step by step. When you are finished, give your answer in this format: <answer>(your answer)</answer>.
# Problem
Using the numbers in the list [21, 80, 46], create an equation that equals 105. You can use basic arithmetic operations (+, -, *, /) and each number can o... | 46 + 80 - 21 | countdown_3arg | countdown | [
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"Answer the following problem. Explain your reasoning step by step. When you are finished, give your(...TRUNCATED) | 86 + 69 - 52 | countdown_3arg | countdown | [{"content":"Answer the following problem. Explain your reasoning step by step. When you are finishe(...TRUNCATED) | [] | [] | "{\"metadata\": \"{\\\"source_dataset\\\": \\\"countdown\\\", \\\"source_index\\\": 5005, \\\"number(...TRUNCATED) | test | "{\"source_dataset\": \"countdown\", \"source_index\": 5005, \"numbers\": [86, 69, 52], \"target\": (...TRUNCATED) | ["Rewritten Question:\n\nCreate an equation using the numbers from the given set {86, 69, 52} that e(...TRUNCATED) | [
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] | [["(38 + 40) + 46"],["(46 - 40) * 38 = 124"],["Step 1: 46 * 40 = 1840\nStep 2: 1840 - 40 = 1800\nSte(...TRUNCATED) | "[[{\"pattern_used\": \"answer tag\", \"confidence\": 1.0, \"position\": 963, \"span_text\": \"(38 +(...TRUNCATED) | "[[{\"is_correct\": true, \"error\": null, \"answer_block\": \"(38 + 40) + 46\", \"final_answer\": 1(...TRUNCATED) | {"flips_by":[0,0,0,0],"flips_total":0,"num_correct":1,"pass_at_n":1,"percent_correct":0.25,"skill_co(...TRUNCATED) | 2025-11-08 | test | main | TAUR-dev/M-RC-ab_sft_bon_corr_samples-sft | 0 | eval_sft | 1 | 2025-11-08T21:07:01.887604 | TAUR-dev/D-EVAL__standard_eval_v3__FinEval_16k_fulleval_3args_STaR-SFT-countdown_3arg-eval_sft |
"Answer the following problem. Explain your reasoning step by step. When you are finished, give your(...TRUNCATED) | 19 + 92 + 21 | countdown_3arg | countdown | [{"content":"Answer the following problem. Explain your reasoning step by step. When you are finishe(...TRUNCATED) | [] | [] | "{\"metadata\": \"{\\\"source_dataset\\\": \\\"countdown\\\", \\\"source_index\\\": 5009, \\\"number(...TRUNCATED) | test | "{\"source_dataset\": \"countdown\", \"source_index\": 5009, \"numbers\": [92, 21, 19], \"target\": (...TRUNCATED) | ["To solve for 132 using the numbers 92, 21, and 19, we need to find a combination of these numbers (...TRUNCATED) | [
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"(92 + 21) + 19 = 132",
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"(92 + 21) + 19 = 132"
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[
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] | "[[{\"pattern_used\": \"answer tag\", \"confidence\": 1.0, \"position\": 1594, \"span_text\": \"(92 (...TRUNCATED) | "[[{\"is_correct\": true, \"error\": null, \"answer_block\": \"(92 + 21) + 19 = 132\", \"final_answe(...TRUNCATED) | {"flips_by":[0,0,0,0],"flips_total":0,"num_correct":3,"pass_at_n":1,"percent_correct":0.75,"skill_co(...TRUNCATED) | 2025-11-08 | test | main | TAUR-dev/M-RC-ab_sft_bon_corr_samples-sft | 0 | eval_sft | 1 | 2025-11-08T21:07:01.887607 | TAUR-dev/D-EVAL__standard_eval_v3__FinEval_16k_fulleval_3args_STaR-SFT-countdown_3arg-eval_sft |
"Answer the following problem. Explain your reasoning step by step. When you are finished, give your(...TRUNCATED) | 23*(21 - 7) | countdown_3arg | countdown | [{"content":"Answer the following problem. Explain your reasoning step by step. When you are finishe(...TRUNCATED) | [] | [] | "{\"metadata\": \"{\\\"source_dataset\\\": \\\"countdown\\\", \\\"source_index\\\": 5010, \\\"number(...TRUNCATED) | test | "{\"source_dataset\": \"countdown\", \"source_index\": 5010, \"numbers\": [23, 21, 7], \"target\": 3(...TRUNCATED) | ["Rewritten Question:\n\nCreate an equation using the numbers from the set {23, 21, 7} that equals e(...TRUNCATED) | [
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] | "[[{\"pattern_used\": \"answer tag\", \"confidence\": 1.0, \"position\": 292, \"span_text\": \"((23 (...TRUNCATED) | "[[{\"is_correct\": false, \"error\": \"Expression does not equal stated result\", \"answer_block\":(...TRUNCATED) | {"flips_by":[0,0,0,0],"flips_total":0,"num_correct":0,"pass_at_n":0,"percent_correct":0.0,"skill_cou(...TRUNCATED) | 2025-11-08 | test | main | TAUR-dev/M-RC-ab_sft_bon_corr_samples-sft | 0 | eval_sft | 1 | 2025-11-08T21:07:01.887609 | TAUR-dev/D-EVAL__standard_eval_v3__FinEval_16k_fulleval_3args_STaR-SFT-countdown_3arg-eval_sft |
End of preview. Expand in Data Studio
Experiment Tracker: FinEval_16k_fulleval_3args_STaR-SFT-countdown_3arg
Experiment Description: Evaluation experiment for task countdown_3arg from FinEval_16k_fulleval_3args_STaR-SFT
Start Time: 2025-11-08T20:36:19.708662
Tracker Dataset: TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_STaR-SFT-countdown_3arg__v1
Stages Completed
Total stages: 1
Models Created
Dataset Configurations
This tracker dataset contains the following configurations with immediate upload as stages complete:
Training Data (Complete Datasets)
Hyperparameters (Complete Configurations)
Logs (Stage-Specific)
Evaluation Results (Complete with Annotations)
Metadata
- experiment_metadata: Timeline and stage information
Usage
Load specific configurations with:
from datasets import load_dataset
# Load experiment metadata
metadata = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_STaR-SFT-countdown_3arg__v1', 'experiment_metadata')
# Load complete training datasets
sft_data = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_STaR-SFT-countdown_3arg__v1', 'training_data__sft')
sft_metadata = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_STaR-SFT-countdown_3arg__v1', 'training_data__sft_metadata')
# Load complete configurations
sft_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_STaR-SFT-countdown_3arg__v1', 'hyperparameters__sft')
rl_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_STaR-SFT-countdown_3arg__v1', 'hyperparameters__rl')
# Load stage-specific logs
sft_logs = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_STaR-SFT-countdown_3arg__v1', 'logs__sft')
rl_logs = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_STaR-SFT-countdown_3arg__v1', 'logs__rl')
# Load evaluation results with annotations
sft_eval_results = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_STaR-SFT-countdown_3arg__v1', 'evals_eval_sft')
rl_eval_results = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_STaR-SFT-countdown_3arg__v1', 'evals_eval_rl')
Models
Registry
All models from this experiment are automatically registered in the SkillFactory Model Registry with:
- Complete training configuration (hyperparameters, datasets, methods)
- Experiment lineage (links back to this tracker dataset)
- Stage-specific metadata (SFT vs RL training details)
- Structured input data references (training datasets and configurations)
Registry entries follow the naming pattern: Model - FinEval_16k_fulleval_3args_STaR-SFT-countdown_3arg - {stage_name} - {SFT/RL}
Generated by SkillFactory Experiment Management System All artifacts uploaded immediately as stages complete with perfect data provenance
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