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4793 x 9915 | 47522595 | longmult_4dig | longmult | [
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"To solve the multiplication of two large numbers like \\(4793 \\times 9915\\), we can use various methods such as long multiplication or breaking down one number into smaller parts that make it easier to handle. Let's explore both approaches:\n\n### Long Multiplication Approach\nWe'll multiply each digit of 4793 b... | [
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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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} | 2025-11-10 | test | main | TAUR-dev/M-AT_star_sft-sft | 0 | eval_sft | 1 | 2025-11-10T04:04:09.123634 | TAUR-dev/D-EVAL__standard_eval_v3__FinEval_16k_fulleval_AT_STAR-SFT-longmult_4dig-eval_sft |
8344 x 6174 | 51515856 | 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?\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} | [
"To solve the multiplication of \\(8344\\) and \\(6174\\), we can use various methods such as long multiplication or breaking down one number into simpler parts. Let's explore both approaches:\n\n### Long Multiplication Approach\n\nFirst, let’s align the numbers vertically for clarity:\n```\n 8344\n × 6174... | [
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} | 2025-11-10 | test | main | TAUR-dev/M-AT_star_sft-sft | 0 | eval_sft | 1 | 2025-11-10T04:04:09.123636 | TAUR-dev/D-EVAL__standard_eval_v3__FinEval_16k_fulleval_AT_STAR-SFT-longmult_4dig-eval_sft |
5560 x 2589 | 14394840 | longmult_4dig | longmult | [
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8481 x 3516 | 29819196 | longmult_4dig | longmult | [
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7176 x 7208 | 51724608 | longmult_4dig | longmult | [
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7493 x 2187 | 16387191 | longmult_4dig | longmult | [
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5644 x 8077 | 45586588 | longmult_4dig | longmult | [
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4389 x 5248 | 23033472 | longmult_4dig | longmult | [
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9077 x 7337 | 66597949 | longmult_4dig | longmult | [
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8360 x 7744 | 64739840 | longmult_4dig | longmult | [
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8201 x 3484 | 28572284 | longmult_4dig | longmult | [
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9961 x 4055 | 40391855 | longmult_4dig | longmult | [
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Experiment Tracker: FinEval_16k_fulleval_AT_STAR-SFT-longmult_4dig
Experiment Description: Evaluation experiment for task longmult_4dig from FinEval_16k_fulleval_AT_STAR-SFT
Start Time: 2025-11-10T03:42:57.154968
Tracker Dataset: TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_AT_STAR-SFT-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_AT_STAR-SFT-longmult_4dig__v1', 'experiment_metadata')
# Load complete training datasets
sft_data = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_AT_STAR-SFT-longmult_4dig__v1', 'training_data__sft')
sft_metadata = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_AT_STAR-SFT-longmult_4dig__v1', 'training_data__sft_metadata')
# Load complete configurations
sft_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_AT_STAR-SFT-longmult_4dig__v1', 'hyperparameters__sft')
rl_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_AT_STAR-SFT-longmult_4dig__v1', 'hyperparameters__rl')
# Load stage-specific logs
sft_logs = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_AT_STAR-SFT-longmult_4dig__v1', 'logs__sft')
rl_logs = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_AT_STAR-SFT-longmult_4dig__v1', 'logs__rl')
# Load evaluation results with annotations
sft_eval_results = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_AT_STAR-SFT-longmult_4dig__v1', 'evals_eval_sft')
rl_eval_results = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_AT_STAR-SFT-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_AT_STAR-SFT-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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