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61662 x 44241 | 2727988542 | longmult_5dig | longmult | [
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... | 2025-11-09 | test | main | TAUR-dev/M-0918__random_3args_grpo-rl | 0 | eval_rl | 1 | 2025-11-09T12:22:23.686768 | TAUR-dev/D-EVAL__standard_eval_v3__FinEval_16k_fulleval_3args_Random-RL-longmult_5dig-eval_rl |
98270 x 48469 | 4763048630 | longmult_5dig | longmult | [
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... | 2025-11-09 | test | main | TAUR-dev/M-0918__random_3args_grpo-rl | 0 | eval_rl | 1 | 2025-11-09T12:22:23.686778 | TAUR-dev/D-EVAL__standard_eval_v3__FinEval_16k_fulleval_3args_Random-RL-longmult_5dig-eval_rl |
85574 x 60628 | 5188180472 | longmult_5dig | longmult | [
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... | 2025-11-09 | test | main | TAUR-dev/M-0918__random_3args_grpo-rl | 0 | eval_rl | 1 | 2025-11-09T12:22:23.686780 | TAUR-dev/D-EVAL__standard_eval_v3__FinEval_16k_fulleval_3args_Random-RL-longmult_5dig-eval_rl |
87369 x 14157 | 1236882933 | longmult_5dig | longmult | [
{
"content": "Answer the following problem. Explain your reasoning step by step. When you are finished, give your answer in this format: <answer>(your answer)</answer>.\n\n# Problem\nWhat is the solution to the multiplication equation below?\n87369 x 14157\n\nGive your answer in the following format:\n<answer>\... | [] | [] | {"metadata": "{\"arg1\": 87369, \"arg2\": 14157, \"solution\": 1236882933}", "task_source": "longmult"} | test | {"arg1": 87369, "arg2": 14157, "solution": 1236882933} | [
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... | 2025-11-09 | test | main | TAUR-dev/M-0918__random_3args_grpo-rl | 0 | eval_rl | 1 | 2025-11-09T12:22:23.686781 | TAUR-dev/D-EVAL__standard_eval_v3__FinEval_16k_fulleval_3args_Random-RL-longmult_5dig-eval_rl |
52577 x 84823 | 4459738871 | longmult_5dig | longmult | [
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"content": "Answer the following problem. Explain your reasoning step by step. When you are finished, give your answer in this format: <answer>(your answer)</answer>.\n\n# Problem\nWhat is the solution to the multiplication equation below?\n52577 x 84823\n\nGive your answer in the following format:\n<answer>\... | [] | [] | {"metadata": "{\"arg1\": 52577, \"arg2\": 84823, \"solution\": 4459738871}", "task_source": "longmult"} | test | {"arg1": 52577, "arg2": 84823, "solution": 4459738871} | [
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... | 2025-11-09 | test | main | TAUR-dev/M-0918__random_3args_grpo-rl | 0 | eval_rl | 1 | 2025-11-09T12:22:23.686783 | TAUR-dev/D-EVAL__standard_eval_v3__FinEval_16k_fulleval_3args_Random-RL-longmult_5dig-eval_rl |
28441 x 57792 | 1643662272 | longmult_5dig | longmult | [
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Experiment Tracker: FinEval_16k_fulleval_3args_Random-RL-longmult_5dig
Experiment Description: Evaluation experiment for task longmult_5dig from FinEval_16k_fulleval_3args_Random-RL
Start Time: 2025-11-09T12:00:40.786119
Tracker Dataset: TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_Random-RL-longmult_5dig__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_Random-RL-longmult_5dig__v1', 'experiment_metadata')
# Load complete training datasets
sft_data = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_Random-RL-longmult_5dig__v1', 'training_data__sft')
sft_metadata = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_Random-RL-longmult_5dig__v1', 'training_data__sft_metadata')
# Load complete configurations
sft_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_Random-RL-longmult_5dig__v1', 'hyperparameters__sft')
rl_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_Random-RL-longmult_5dig__v1', 'hyperparameters__rl')
# Load stage-specific logs
sft_logs = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_Random-RL-longmult_5dig__v1', 'logs__sft')
rl_logs = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_Random-RL-longmult_5dig__v1', 'logs__rl')
# Load evaluation results with annotations
sft_eval_results = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_Random-RL-longmult_5dig__v1', 'evals_eval_sft')
rl_eval_results = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_Random-RL-longmult_5dig__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_Random-RL-longmult_5dig - {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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