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756 x 322 | 243432 | longmult_3dig | longmult | [
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726 x 135 | 98010 | longmult_3dig | longmult | [
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520 x 133 | 69160 | longmult_3dig | longmult | [
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420 x 680 | 285600 | longmult_3dig | longmult | [
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593 x 797 | 472621 | longmult_3dig | longmult | [
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} | 2025-10-27 | test | main | TAUR-dev/M-sft_exp_1e_zayneprompts_v2-sft | 0 | eval_sft | 1 | 2025-10-27T05:53:31.204001 | TAUR-dev/D-EVAL__standard_eval_v3__FinEval_16k_fulleval_3args_ours_sft-longmult_3dig-eval_sft |
451 x 158 | 71258 | longmult_3dig | longmult | [{"content":"Answer the following problem. Explain your reasoning step by step. When you are finishe(...TRUNCATED) | [] | [] | "{\"metadata\": \"{\\\"arg1\\\": 451, \\\"arg2\\\": 158, \\\"solution\\\": 71258}\", \"task_source\"(...TRUNCATED) | test | {"arg1": 451, "arg2": 158, "solution": 71258} | ["<think>\n<sample>\nTo solve the multiplication equation \\( 451 \\times 158 \\), we can break it d(...TRUNCATED) | [
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414 x 772 | 319608 | longmult_3dig | longmult | [{"content":"Answer the following problem. Explain your reasoning step by step. When you are finishe(...TRUNCATED) | [] | [] | "{\"metadata\": \"{\\\"arg1\\\": 414, \\\"arg2\\\": 772, \\\"solution\\\": 319608}\", \"task_source\(...TRUNCATED) | test | {"arg1": 414, "arg2": 772, "solution": 319608} | ["<think>\n<sample>\nTo solve the multiplication equation \\( 414 \\times 772 \\), we will follow th(...TRUNCATED) | [
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End of preview. Expand in Data Studio
Experiment Tracker: FinEval_16k_fulleval_3args_ours_sft-longmult_3dig
Experiment Description: Evaluation experiment for task longmult_3dig from FinEval_16k_fulleval_3args_ours_sft
Start Time: 2025-10-27T05:35:13.914309
Tracker Dataset: TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_ours_sft-longmult_3dig__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_ours_sft-longmult_3dig__v1', 'experiment_metadata')
# Load complete training datasets
sft_data = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_ours_sft-longmult_3dig__v1', 'training_data__sft')
sft_metadata = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_ours_sft-longmult_3dig__v1', 'training_data__sft_metadata')
# Load complete configurations
sft_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_ours_sft-longmult_3dig__v1', 'hyperparameters__sft')
rl_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_ours_sft-longmult_3dig__v1', 'hyperparameters__rl')
# Load stage-specific logs
sft_logs = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_ours_sft-longmult_3dig__v1', 'logs__sft')
rl_logs = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_ours_sft-longmult_3dig__v1', 'logs__rl')
# Load evaluation results with annotations
sft_eval_results = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_ours_sft-longmult_3dig__v1', 'evals_eval_sft')
rl_eval_results = load_dataset('TAUR-dev/D-ExpTracker__FinEval_16k_fulleval_3args_ours_sft-longmult_3dig__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_ours_sft-longmult_3dig - {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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