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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
4793 x 9915 | 47522595 | longmult_4dig | longmult | [
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4507 x 8243 | 37151201 | longmult_4dig | longmult | [
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7645 x 2867 | 21918215 | longmult_4dig | 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?\n7645 x 2867\n\nGive your answer in the following format:\n<answer>\n(... | [] | [] | {"metadata": "{\"arg1\": 7645, \"arg2\": 2867, \"solution\": 21918215}", "task_source": "longmult"} | test | {"arg1": 7645, "arg2": 2867, "solution": 21918215} | [
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} | 2025-11-27 | test | main | TAUR-dev/M-1119_newmodels__qwen7b_sft1k_ours-rl@checkpoint-step-150 | 0 | eval_rl | 1 | 2025-11-27T19:38:44.358049 | TAUR-dev/D-EVAL__standard_eval_v3__FinEval_16k_fulleval_3arg_OT_ours_1k-at150-RL-longmult_4dig-eval_rl |
8344 x 6174 | 51515856 | longmult_4dig | 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?\n8344 x 6174\n\nGive your answer in the following format:\n<answer>\n(... | [] | [] | {"metadata": "{\"arg1\": 8344, \"arg2\": 6174, \"solution\": 51515856}", "task_source": "longmult"} | test | {"arg1": 8344, "arg2": 6174, "solution": 51515856} | [
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5560 x 2589 | 14394840 | longmult_4dig | 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?\n5560 x 2589\n\nGive your answer in the following format:\n<answer>\n(... | [] | [] | {"metadata": "{\"arg1\": 5560, \"arg2\": 2589, \"solution\": 14394840}", "task_source": "longmult"} | test | {"arg1": 5560, "arg2": 2589, "solution": 14394840} | [
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5291 x 7587 | 40142817 | longmult_4dig | longmult | [
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7176 x 7208 | 51724608 | longmult_4dig | longmult | [{"content":"Answer the following problem. Explain your reasoning step by step. When you are finishe(...TRUNCATED) | [] | [] | "{\"metadata\": \"{\\\"arg1\\\": 7176, \\\"arg2\\\": 7208, \\\"solution\\\": 51724608}\", \"task_sou(...TRUNCATED) | test | {"arg1": 7176, "arg2": 7208, "solution": 51724608} | ["<think>\n<sample>\nTo find the product of \\(7176 \\times 7208\\), we can use the standard multipl(...TRUNCATED) | [
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Experiment Tracker: FinEval_16k_fulleval_3arg_OT_ours_1k-at150-RL-longmult_4dig
Experiment Description: Evaluation experiment for task longmult_4dig from FinEval_16k_fulleval_3arg_OT_ours_1k-at150-RL
Start Time: 2025-11-27T19:12:36.381048
Tracker Dataset: TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3arg_OT_ours_1k-at150-RL-longmult_4dig__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_3arg_OT_ours_1k-at150-RL-longmult_4dig__v1', 'experiment_metadata')
# Load complete training datasets
sft_data = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3arg_OT_ours_1k-at150-RL-longmult_4dig__v1', 'training_data__sft')
sft_metadata = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3arg_OT_ours_1k-at150-RL-longmult_4dig__v1', 'training_data__sft_metadata')
# Load complete configurations
sft_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3arg_OT_ours_1k-at150-RL-longmult_4dig__v1', 'hyperparameters__sft')
rl_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3arg_OT_ours_1k-at150-RL-longmult_4dig__v1', 'hyperparameters__rl')
# Load stage-specific logs
sft_logs = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3arg_OT_ours_1k-at150-RL-longmult_4dig__v1', 'logs__sft')
rl_logs = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3arg_OT_ours_1k-at150-RL-longmult_4dig__v1', 'logs__rl')
# Load evaluation results with annotations
sft_eval_results = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3arg_OT_ours_1k-at150-RL-longmult_4dig__v1', 'evals_eval_sft')
rl_eval_results = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3arg_OT_ours_1k-at150-RL-longmult_4dig__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_3arg_OT_ours_1k-at150-RL-longmult_4dig - {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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