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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 [68, 97, 78, 16, 66], create an equation that equals 137. You can use basic arithmetic operations (+, -, *, /) and each numb... | 97 - 16 - 78 + 66 + 68 | countdown_5arg | countdown | [
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... | 2025-11-09 | test | main | TAUR-dev/M-0909__0epoch_3args_grpo-rl | 0 | eval_rl | 1 | 2025-11-09T06:24:47.249343 | TAUR-dev/D-EVAL__standard_eval_v3__FinEval_16k_fulleval_3args_InstOnly-RL-countdown_5arg-eval_rl |
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"None of the above"
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] | "[[], [], [], [{\"pattern_used\": \"answer tag\", \"confidence\": 1.0, \"position\": 8729, \"span_te(...TRUNCATED) | "[[], [], [], [{\"is_correct\": false, \"error\": \"Could not evaluate expression\", \"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) | 2025-11-09 | test | main | TAUR-dev/M-0909__0epoch_3args_grpo-rl | 0 | eval_rl | 1 | 2025-11-09T06:24:47.249369 | TAUR-dev/D-EVAL__standard_eval_v3__FinEval_16k_fulleval_3args_InstOnly-RL-countdown_5arg-eval_rl |
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Experiment Tracker: FinEval_16k_fulleval_3args_InstOnly-RL-countdown_5arg
Experiment Description: Evaluation experiment for task countdown_5arg from FinEval_16k_fulleval_3args_InstOnly-RL
Start Time: 2025-11-09T01:52:56.657755
Tracker Dataset: TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_InstOnly-RL-countdown_5arg__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_InstOnly-RL-countdown_5arg__v1', 'experiment_metadata')
# Load complete training datasets
sft_data = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_InstOnly-RL-countdown_5arg__v1', 'training_data__sft')
sft_metadata = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_InstOnly-RL-countdown_5arg__v1', 'training_data__sft_metadata')
# Load complete configurations
sft_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_InstOnly-RL-countdown_5arg__v1', 'hyperparameters__sft')
rl_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_InstOnly-RL-countdown_5arg__v1', 'hyperparameters__rl')
# Load stage-specific logs
sft_logs = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_InstOnly-RL-countdown_5arg__v1', 'logs__sft')
rl_logs = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_InstOnly-RL-countdown_5arg__v1', 'logs__rl')
# Load evaluation results with annotations
sft_eval_results = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_InstOnly-RL-countdown_5arg__v1', 'evals_eval_sft')
rl_eval_results = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_InstOnly-RL-countdown_5arg__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_InstOnly-RL-countdown_5arg - {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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