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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 [37, 27, 3, 84, 5, 80], create an equation that equals 152. You can use basic arithmetic operations (+, -, *, /) and each nu... | 84 + 80 - 37 + 3 - 5 + 27 | countdown_6arg | countdown | [
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... | 2025-11-02 | test | main | TAUR-dev/M-r1_distill_baseline-rl | 0 | eval_rl | 1 | 2025-11-02T20:46:42.558793 | TAUR-dev/D-EVAL__standard_eval_v3__FinEval_16k_fulleval_3args_r1distill_rl-countdown_6arg-eval_rl |
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"Answer the following problem. Explain your reasoning step by step. When you are finished, give your(...TRUNCATED) | 9*56 - 71 - 59 + 74 + 44 | countdown_6arg | countdown | [{"content":"Answer the following problem. Explain your reasoning step by step. When you are finishe(...TRUNCATED) | [] | [] | "{\"metadata\": \"{\\\"source_dataset\\\": \\\"countdown\\\", \\\"source_index\\\": 5, \\\"numbers\\(...TRUNCATED) | test | "{\"source_dataset\": \"countdown\", \"source_index\": 5, \"numbers\": [74, 44, 56, 9, 59, 71], \"ta(...TRUNCATED) | ["<think>\nI have the numbers [74, 44, 56, 9, 59, 71] and need to make an equation that equals 492 u(...TRUNCATED) | [
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"Answer the following problem. Explain your reasoning step by step. When you are finished, give your(...TRUNCATED) | 27*(52 - 12 - 37 + 4 + 10) | countdown_6arg | countdown | [{"content":"Answer the following problem. Explain your reasoning step by step. When you are finishe(...TRUNCATED) | [] | [] | "{\"metadata\": \"{\\\"source_dataset\\\": \\\"countdown\\\", \\\"source_index\\\": 19, \\\"numbers\(...TRUNCATED) | test | "{\"source_dataset\": \"countdown\", \"source_index\": 19, \"numbers\": [27, 4, 37, 10, 12, 52], \"t(...TRUNCATED) | ["<think>\nI have the numbers [27, 4, 37, 10, 12, 52] and need to make an equation that equals 459 u(...TRUNCATED) | [
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"Answer the following problem. Explain your reasoning step by step. When you are finished, give your(...TRUNCATED) | 34*22 - 67 - 84 + 3 - 55 | countdown_6arg | countdown | [{"content":"Answer the following problem. Explain your reasoning step by step. When you are finishe(...TRUNCATED) | [] | [] | "{\"metadata\": \"{\\\"source_dataset\\\": \\\"countdown\\\", \\\"source_index\\\": 20, \\\"numbers\(...TRUNCATED) | test | "{\"source_dataset\": \"countdown\", \"source_index\": 20, \"numbers\": [3, 55, 22, 34, 84, 67], \"t(...TRUNCATED) | ["<think>\nI have the numbers [3, 55, 22, 34, 84, 67] and need to make an equation that equals 545 u(...TRUNCATED) | [
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"Answer the following problem. Explain your reasoning step by step. When you are finished, give your(...TRUNCATED) | 52*(16 + 81 - 79) - 69 - 88 | countdown_6arg | countdown | [{"content":"Answer the following problem. Explain your reasoning step by step. When you are finishe(...TRUNCATED) | [] | [] | "{\"metadata\": \"{\\\"source_dataset\\\": \\\"countdown\\\", \\\"source_index\\\": 22, \\\"numbers\(...TRUNCATED) | test | "{\"source_dataset\": \"countdown\", \"source_index\": 22, \"numbers\": [81, 79, 88, 69, 52, 16], \"(...TRUNCATED) | ["<think>\nI have the numbers [81, 79, 88, 69, 52, 16] and need to make an equation that equals 779 (...TRUNCATED) | [
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"Answer the following problem. Explain your reasoning step by step. When you are finished, give your(...TRUNCATED) | 28*(37 - 19 + 26 + 19 - 40) | countdown_6arg | countdown | [{"content":"Answer the following problem. Explain your reasoning step by step. When you are finishe(...TRUNCATED) | [] | [] | "{\"metadata\": \"{\\\"source_dataset\\\": \\\"countdown\\\", \\\"source_index\\\": 27, \\\"numbers\(...TRUNCATED) | test | "{\"source_dataset\": \"countdown\", \"source_index\": 27, \"numbers\": [19, 19, 37, 26, 40, 28], \"(...TRUNCATED) | ["<think>\nI have the numbers [19, 19, 37, 26, 40, 28] and need to make an equation that equals 644 (...TRUNCATED) | [
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End of preview. Expand in Data Studio
Experiment Tracker: FinEval_16k_fulleval_3args_r1distill_rl-countdown_6arg
Experiment Description: Evaluation experiment for task countdown_6arg from FinEval_16k_fulleval_3args_r1distill_rl
Start Time: 2025-11-02T19:25:58.572949
Tracker Dataset: TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_r1distill_rl-countdown_6arg__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_r1distill_rl-countdown_6arg__v1', 'experiment_metadata')
# Load complete training datasets
sft_data = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_r1distill_rl-countdown_6arg__v1', 'training_data__sft')
sft_metadata = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_r1distill_rl-countdown_6arg__v1', 'training_data__sft_metadata')
# Load complete configurations
sft_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_r1distill_rl-countdown_6arg__v1', 'hyperparameters__sft')
rl_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_r1distill_rl-countdown_6arg__v1', 'hyperparameters__rl')
# Load stage-specific logs
sft_logs = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_r1distill_rl-countdown_6arg__v1', 'logs__sft')
rl_logs = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_r1distill_rl-countdown_6arg__v1', 'logs__rl')
# Load evaluation results with annotations
sft_eval_results = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_r1distill_rl-countdown_6arg__v1', 'evals_eval_sft')
rl_eval_results = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_r1distill_rl-countdown_6arg__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_r1distill_rl-countdown_6arg - {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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