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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
4793 x 9915 | 47522595 | longmult_4dig | longmult | [
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... | 2025-11-02 | test | main | TAUR-dev/M-r1_translated_BASELINE-sft | 0 | eval_sft | 1 | 2025-11-02T02:01:10.931305 | TAUR-dev/D-EVAL__standard_eval_v3__Fin16kEval_SFT_r1_translated-longmult_4dig-eval_sft |
4507 x 8243 | 37151201 | longmult_4dig | longmult | [
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... | 2025-11-02 | test | main | TAUR-dev/M-r1_translated_BASELINE-sft | 0 | eval_sft | 1 | 2025-11-02T02:01:10.931316 | TAUR-dev/D-EVAL__standard_eval_v3__Fin16kEval_SFT_r1_translated-longmult_4dig-eval_sft |
7645 x 2867 | 21918215 | longmult_4dig | longmult | [
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... | 2025-11-02 | test | main | TAUR-dev/M-r1_translated_BASELINE-sft | 0 | eval_sft | 1 | 2025-11-02T02:01:10.931318 | TAUR-dev/D-EVAL__standard_eval_v3__Fin16kEval_SFT_r1_translated-longmult_4dig-eval_sft |
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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... | 2025-11-02 | test | main | TAUR-dev/M-r1_translated_BASELINE-sft | 0 | eval_sft | 1 | 2025-11-02T02:01:10.931319 | TAUR-dev/D-EVAL__standard_eval_v3__Fin16kEval_SFT_r1_translated-longmult_4dig-eval_sft |
5560 x 2589 | 14394840 | longmult_4dig | longmult | [{"content":"Answer the following problem. Explain your reasoning step by step. When you are finishe(...TRUNCATED) | [] | [] | "{\"metadata\": \"{\\\"arg1\\\": 5560, \\\"arg2\\\": 2589, \\\"solution\\\": 14394840}\", \"task_sou(...TRUNCATED) | test | {"arg1": 5560, "arg2": 2589, "solution": 14394840} | ["<think><sample>\nFirst, I need to multiply these two numbers: 5560 and 2589.\nI can't do that dire(...TRUNCATED) | [
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5291 x 7587 | 40142817 | longmult_4dig | longmult | [{"content":"Answer the following problem. Explain your reasoning step by step. When you are finishe(...TRUNCATED) | [] | [] | "{\"metadata\": \"{\\\"arg1\\\": 5291, \\\"arg2\\\": 7587, \\\"solution\\\": 40142817}\", \"task_sou(...TRUNCATED) | test | {"arg1": 5291, "arg2": 7587, "solution": 40142817} | ["<think><sample>\nFirst, I need to multiply 5291 and 7587. That should be straightforward.\n<answer(...TRUNCATED) | [
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8481 x 3516 | 29819196 | longmult_4dig | longmult | [{"content":"Answer the following problem. Explain your reasoning step by step. When you are finishe(...TRUNCATED) | [] | [] | "{\"metadata\": \"{\\\"arg1\\\": 8481, \\\"arg2\\\": 3516, \\\"solution\\\": 29819196}\", \"task_sou(...TRUNCATED) | test | {"arg1": 8481, "arg2": 3516, "solution": 29819196} | ["<think><sample>\nFirst, I need to multiply 8481 by 3516. Let me see how big these numbers are. 848(...TRUNCATED) | [
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] | [[],["(your answer)","(your answer)","29819196","29819196"],["28,000,000","8481 × 3516"],["(your an(...TRUNCATED) | "[[], [{\"pattern_used\": \"answer tag\", \"confidence\": 1.0, \"position\": 1963, \"span_text\": \"(...TRUNCATED) | "[[], [{\"evaluation_method\": \"legacy\", \"legacy_result\": false}, {\"evaluation_method\": \"lega(...TRUNCATED) | {"flips_by":[0,0,0,0],"flips_total":0,"num_correct":1,"pass_at_n":1,"percent_correct":0.25,"skill_co(...TRUNCATED) | 2025-11-02 | test | main | TAUR-dev/M-r1_translated_BASELINE-sft | 0 | eval_sft | 1 | 2025-11-02T02:01:10.931324 | TAUR-dev/D-EVAL__standard_eval_v3__Fin16kEval_SFT_r1_translated-longmult_4dig-eval_sft |
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><sample>\nFirst, I need to multiply these two numbers: 7176 and 7208.\nI should probably us(...TRUNCATED) | [
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7493 x 2187 | 16387191 | longmult_4dig | longmult | [{"content":"Answer the following problem. Explain your reasoning step by step. When you are finishe(...TRUNCATED) | [] | [] | "{\"metadata\": \"{\\\"arg1\\\": 7493, \\\"arg2\\\": 2187, \\\"solution\\\": 16387191}\", \"task_sou(...TRUNCATED) | test | {"arg1": 7493, "arg2": 2187, "solution": 16387191} | ["<think><sample>\nFirst, I need to multiply 7493 by 2187. Let me see how large these numbers are. 7(...TRUNCATED) | [
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] | [["479552"],["16470001","16470001","16470001"],["30484600","1356871110","1356871110"],["123456789","(...TRUNCATED) | "[[{\"pattern_used\": \"answer tag\", \"confidence\": 1.0, \"position\": 3388, \"span_text\": \"4795(...TRUNCATED) | "[[{\"evaluation_method\": \"legacy\", \"legacy_result\": false}], [{\"evaluation_method\": \"legacy(...TRUNCATED) | {"flips_by":[0,0,0,0],"flips_total":0,"num_correct":0,"pass_at_n":0,"percent_correct":0.0,"skill_cou(...TRUNCATED) | 2025-11-02 | test | main | TAUR-dev/M-r1_translated_BASELINE-sft | 0 | eval_sft | 1 | 2025-11-02T02:01:10.931328 | TAUR-dev/D-EVAL__standard_eval_v3__Fin16kEval_SFT_r1_translated-longmult_4dig-eval_sft |
5644 x 8077 | 45586588 | longmult_4dig | longmult | [{"content":"Answer the following problem. Explain your reasoning step by step. When you are finishe(...TRUNCATED) | [] | [] | "{\"metadata\": \"{\\\"arg1\\\": 5644, \\\"arg2\\\": 8077, \\\"solution\\\": 45586588}\", \"task_sou(...TRUNCATED) | test | {"arg1": 5644, "arg2": 8077, "solution": 45586588} | ["<think><sample>\nFirst, I need to multiply 5644 and 8077. That should be straightforward, but let (...TRUNCATED) | [
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End of preview. Expand in Data Studio
Experiment Tracker: Fin16kEval_SFT_r1_translated-longmult_4dig
Experiment Description: Evaluation experiment for task longmult_4dig from Fin16kEval_SFT_r1_translated
Start Time: 2025-11-02T01:16:53.272246
Tracker Dataset: TAUR-dev/D-ExpTracker__Fin16kEval_SFT_r1_translated-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__Fin16kEval_SFT_r1_translated-longmult_4dig__v1', 'experiment_metadata')
# Load complete training datasets
sft_data = load_dataset('TAUR-dev/D-ExpTracker__Fin16kEval_SFT_r1_translated-longmult_4dig__v1', 'training_data__sft')
sft_metadata = load_dataset('TAUR-dev/D-ExpTracker__Fin16kEval_SFT_r1_translated-longmult_4dig__v1', 'training_data__sft_metadata')
# Load complete configurations
sft_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__Fin16kEval_SFT_r1_translated-longmult_4dig__v1', 'hyperparameters__sft')
rl_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__Fin16kEval_SFT_r1_translated-longmult_4dig__v1', 'hyperparameters__rl')
# Load stage-specific logs
sft_logs = load_dataset('TAUR-dev/D-ExpTracker__Fin16kEval_SFT_r1_translated-longmult_4dig__v1', 'logs__sft')
rl_logs = load_dataset('TAUR-dev/D-ExpTracker__Fin16kEval_SFT_r1_translated-longmult_4dig__v1', 'logs__rl')
# Load evaluation results with annotations
sft_eval_results = load_dataset('TAUR-dev/D-ExpTracker__Fin16kEval_SFT_r1_translated-longmult_4dig__v1', 'evals_eval_sft')
rl_eval_results = load_dataset('TAUR-dev/D-ExpTracker__Fin16kEval_SFT_r1_translated-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 - Fin16kEval_SFT_r1_translated-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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