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30 x 62 | 1860 | longmult_2dig | longmult | [
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... | 2025-11-02 | test | main | TAUR-dev/M-r1_translated_BASELINE-sft | 0 | eval_sft | 1 | 2025-11-02T01:32:18.077453 | TAUR-dev/D-EVAL__standard_eval_v3__Fin16kEval_SFT_r1_translated-longmult_2dig-eval_sft |
33 x 67 | 2211 | longmult_2dig | longmult | [
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... | 2025-11-02 | test | main | TAUR-dev/M-r1_translated_BASELINE-sft | 0 | eval_sft | 1 | 2025-11-02T01:32:18.077462 | TAUR-dev/D-EVAL__standard_eval_v3__Fin16kEval_SFT_r1_translated-longmult_2dig-eval_sft |
74 x 60 | 4440 | longmult_2dig | longmult | [
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... | 2025-11-02 | test | main | TAUR-dev/M-r1_translated_BASELINE-sft | 0 | eval_sft | 1 | 2025-11-02T01:32:18.077464 | TAUR-dev/D-EVAL__standard_eval_v3__Fin16kEval_SFT_r1_translated-longmult_2dig-eval_sft |
69 x 45 | 3105 | longmult_2dig | longmult | [
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... | 2025-11-02 | test | main | TAUR-dev/M-r1_translated_BASELINE-sft | 0 | eval_sft | 1 | 2025-11-02T01:32:18.077465 | TAUR-dev/D-EVAL__standard_eval_v3__Fin16kEval_SFT_r1_translated-longmult_2dig-eval_sft |
73 x 71 | 5183 | longmult_2dig | longmult | [
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... | 2025-11-02 | test | main | TAUR-dev/M-r1_translated_BASELINE-sft | 0 | eval_sft | 1 | 2025-11-02T01:32:18.077467 | TAUR-dev/D-EVAL__standard_eval_v3__Fin16kEval_SFT_r1_translated-longmult_2dig-eval_sft |
59 x 36 | 2124 | longmult_2dig | longmult | [
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... | 2025-11-02 | test | main | TAUR-dev/M-r1_translated_BASELINE-sft | 0 | eval_sft | 1 | 2025-11-02T01:32:18.077468 | TAUR-dev/D-EVAL__standard_eval_v3__Fin16kEval_SFT_r1_translated-longmult_2dig-eval_sft |
23 x 24 | 552 | longmult_2dig | longmult | [
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... | 2025-11-02 | test | main | TAUR-dev/M-r1_translated_BASELINE-sft | 0 | eval_sft | 1 | 2025-11-02T01:32:18.077470 | TAUR-dev/D-EVAL__standard_eval_v3__Fin16kEval_SFT_r1_translated-longmult_2dig-eval_sft |
47 x 41 | 1927 | longmult_2dig | longmult | [{"content":"Answer the following problem. Explain your reasoning step by step. When you are finishe(...TRUNCATED) | [] | [] | "{\"metadata\": \"{\\\"arg1\\\": 47, \\\"arg2\\\": 41, \\\"solution\\\": 1927}\", \"task_source\": \(...TRUNCATED) | test | {"arg1": 47, "arg2": 41, "solution": 1927} | ["<think><sample>\nFirst, I need to multiply 47 and 41. That seems like a straightforward multiplica(...TRUNCATED) | [
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89 x 46 | 4094 | longmult_2dig | longmult | [{"content":"Answer the following problem. Explain your reasoning step by step. When you are finishe(...TRUNCATED) | [] | [] | "{\"metadata\": \"{\\\"arg1\\\": 89, \\\"arg2\\\": 46, \\\"solution\\\": 4094}\", \"task_source\": \(...TRUNCATED) | test | {"arg1": 89, "arg2": 46, "solution": 4094} | ["<think><sample>\nFirst, I need to multiply these two numbers: 89 and 46.\nI can break it down or u(...TRUNCATED) | [
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30 x 35 | 1050 | longmult_2dig | longmult | [{"content":"Answer the following problem. Explain your reasoning step by step. When you are finishe(...TRUNCATED) | [] | [] | "{\"metadata\": \"{\\\"arg1\\\": 30, \\\"arg2\\\": 35, \\\"solution\\\": 1050}\", \"task_source\": \(...TRUNCATED) | test | {"arg1": 30, "arg2": 35, "solution": 1050} | ["<think><sample>\nFirst, I need to multiply 30 and 35. That seems straightforward.\n<action>\nMulti(...TRUNCATED) | [
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End of preview. Expand in Data Studio
Experiment Tracker: Fin16kEval_SFT_r1_translated-longmult_2dig
Experiment Description: Evaluation experiment for task longmult_2dig from Fin16kEval_SFT_r1_translated
Start Time: 2025-11-02T00:49:08.449702
Tracker Dataset: TAUR-dev/D-ExpTracker__Fin16kEval_SFT_r1_translated-longmult_2dig__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_2dig__v1', 'experiment_metadata')
# Load complete training datasets
sft_data = load_dataset('TAUR-dev/D-ExpTracker__Fin16kEval_SFT_r1_translated-longmult_2dig__v1', 'training_data__sft')
sft_metadata = load_dataset('TAUR-dev/D-ExpTracker__Fin16kEval_SFT_r1_translated-longmult_2dig__v1', 'training_data__sft_metadata')
# Load complete configurations
sft_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__Fin16kEval_SFT_r1_translated-longmult_2dig__v1', 'hyperparameters__sft')
rl_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__Fin16kEval_SFT_r1_translated-longmult_2dig__v1', 'hyperparameters__rl')
# Load stage-specific logs
sft_logs = load_dataset('TAUR-dev/D-ExpTracker__Fin16kEval_SFT_r1_translated-longmult_2dig__v1', 'logs__sft')
rl_logs = load_dataset('TAUR-dev/D-ExpTracker__Fin16kEval_SFT_r1_translated-longmult_2dig__v1', 'logs__rl')
# Load evaluation results with annotations
sft_eval_results = load_dataset('TAUR-dev/D-ExpTracker__Fin16kEval_SFT_r1_translated-longmult_2dig__v1', 'evals_eval_sft')
rl_eval_results = load_dataset('TAUR-dev/D-ExpTracker__Fin16kEval_SFT_r1_translated-longmult_2dig__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_2dig - {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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