--- dataset_info: - config_name: hyperparameters__rl features: - name: stage_name dtype: string - name: stage_number dtype: int64 - name: stage_type dtype: string - name: model_repo_id dtype: string - name: base_model dtype: string - name: timestamp dtype: string - name: verl_parameter_config struct: - name: actor_rollout_ref.actor.fsdp_config.forward_prefetch dtype: bool - name: actor_rollout_ref.actor.optim.lr dtype: float64 - name: actor_rollout_ref.actor.ppo_micro_batch_size_per_gpu dtype: int64 - name: actor_rollout_ref.actor.ppo_mini_batch_size dtype: int64 - name: actor_rollout_ref.actor.strategy dtype: string - name: actor_rollout_ref.model.enable_activation_offload dtype: bool - name: actor_rollout_ref.model.enable_gradient_checkpointing dtype: bool - name: actor_rollout_ref.model.path dtype: string - name: actor_rollout_ref.model.trust_remote_code dtype: bool - name: actor_rollout_ref.model.use_remove_padding dtype: bool - name: actor_rollout_ref.ref.fsdp_config.forward_prefetch dtype: bool - name: actor_rollout_ref.ref.log_prob_micro_batch_size_per_gpu dtype: int64 - name: actor_rollout_ref.rollout.dtype dtype: string - name: actor_rollout_ref.rollout.gpu_memory_utilization dtype: float64 - name: actor_rollout_ref.rollout.log_prob_micro_batch_size_per_gpu dtype: int64 - name: actor_rollout_ref.rollout.max_num_batched_tokens dtype: int64 - name: actor_rollout_ref.rollout.max_num_seqs dtype: int64 - name: actor_rollout_ref.rollout.n dtype: int64 - name: actor_rollout_ref.rollout.tensor_model_parallel_size dtype: int64 - name: algorithm.adv_estimator dtype: string - name: algorithm.kl_ctrl.kl_coef dtype: float64 - name: critic.model.path dtype: string - name: critic.model.trust_remote_code dtype: bool - name: critic.optim.lr dtype: float64 - name: critic.ppo_micro_batch_size_per_gpu dtype: int64 - name: custom_reward_function.name dtype: string - name: custom_reward_function.path dtype: string - name: custom_reward_function.reward_kwargs.complex_format_reward_weight dtype: float64 - name: custom_reward_function.reward_kwargs.final_answer_in_samples_reward_weight dtype: float64 - name: custom_reward_function.reward_kwargs.reflection_correctness_reward_weight dtype: float64 - name: custom_reward_function.reward_kwargs.response_or_sample dtype: string - name: custom_reward_function.reward_kwargs.reward_max dtype: float64 - name: custom_reward_function.reward_kwargs.reward_min dtype: float64 - name: custom_reward_function.reward_kwargs.sample_correctness_reward_weight dtype: float64 - name: custom_reward_function.reward_kwargs.sample_count_penalty_weight dtype: float64 - name: custom_reward_function.reward_kwargs.similarity_penalty_weight dtype: float64 - name: custom_reward_function.reward_kwargs.simple_format_reward_weight dtype: float64 - name: custom_reward_function.reward_kwargs.transition_penalty_weight dtype: float64 - name: custom_reward_function.reward_kwargs.verdict_correctness_reward_weight dtype: float64 - name: data.max_prompt_length dtype: int64 - name: data.max_response_length dtype: int64 - name: data.train_batch_size dtype: int64 - name: data.train_files dtype: string - name: data.val_files dtype: string - name: hydra.job.chdir dtype: bool - name: hydra.output_subdir dtype: string - name: hydra.run.dir dtype: string - name: reward_model.launch_reward_fn_async dtype: bool - name: reward_model.model.fsdp_config.forward_prefetch dtype: bool - name: reward_model.reward_manager dtype: string - name: trainer.default_local_dir dtype: string - name: trainer.experiment_name dtype: string - name: trainer.logger dtype: string - name: trainer.n_gpus_per_node dtype: int64 - name: trainer.nnodes dtype: int64 - name: trainer.project_name dtype: string - name: trainer.resume_mode dtype: string - name: trainer.save_freq dtype: int64 - name: trainer.test_freq dtype: int64 - name: trainer.total_epochs dtype: int64 - name: trainer.val_before_train dtype: bool splits: - name: train num_bytes: 1323 num_examples: 1 download_size: 41358 dataset_size: 1323 - config_name: logs__verl_rl features: - name: timestamp dtype: string - name: end_timestamp dtype: string - name: stage_name dtype: string - name: stage_number dtype: int64 - name: level dtype: string - name: message dtype: string - name: stdout_content dtype: string - name: stderr_content dtype: string - name: experiment_name dtype: string - name: elapsed_time_seconds dtype: float64 - name: stage_complete dtype: bool splits: - name: train num_bytes: 5612809 num_examples: 2 download_size: 907645 dataset_size: 5612809 - config_name: metadata features: - name: experiment_name dtype: string - name: start_time dtype: string - name: description dtype: string - name: base_org dtype: string - name: stage_number dtype: string - name: stage_type dtype: string - name: status dtype: string splits: - name: train num_bytes: 2544 num_examples: 7 download_size: 4542 dataset_size: 2544 - config_name: training_data__rl_metadata features: - name: stage_name dtype: string - name: stage_number dtype: int64 - name: timestamp dtype: string - name: original_dataset_id dtype: string - name: dataset_type dtype: string - name: rl_training_splits list: string - name: rl_validation_splits list: string - name: rl_configs list: string - name: usage dtype: string splits: - name: train num_bytes: 201 num_examples: 1 download_size: 4986 dataset_size: 201 configs: - config_name: hyperparameters__rl data_files: - split: train path: hyperparameters__rl/train-* - config_name: logs__verl_rl data_files: - split: train path: logs__verl_rl/train-* - config_name: metadata data_files: - split: train path: metadata/train-* - config_name: training_data__rl_metadata data_files: - split: train path: training_data__rl_metadata/train-* --- # Experiment Tracker: 1023_longmult__0epoch_longmult3dig **Experiment Description:** Experiment: 1023_longmult__0epoch_longmult3dig **Start Time:** 2025-10-24T14:32:01.782278 **Tracker Dataset:** [TAUR-dev/D-ExpTracker__1023_longmult__0epoch_longmult3dig__v1](https://huggingface.co/datasets/TAUR-dev/D-ExpTracker__1023_longmult__0epoch_longmult3dig__v1) ## Stages Completed Total stages: 1 ## Models Created - **rl**: [TAUR-dev/M-1023_longmult__0epoch_longmult3dig-rl](https://huggingface.co/TAUR-dev/M-1023_longmult__0epoch_longmult3dig-rl) ## 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: ```python from datasets import load_dataset # Load experiment metadata metadata = load_dataset('TAUR-dev/D-ExpTracker__1023_longmult__0epoch_longmult3dig__v1', 'experiment_metadata') # Load complete training datasets sft_data = load_dataset('TAUR-dev/D-ExpTracker__1023_longmult__0epoch_longmult3dig__v1', 'training_data__sft') sft_metadata = load_dataset('TAUR-dev/D-ExpTracker__1023_longmult__0epoch_longmult3dig__v1', 'training_data__sft_metadata') # Load complete configurations sft_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__1023_longmult__0epoch_longmult3dig__v1', 'hyperparameters__sft') rl_hyperparams = load_dataset('TAUR-dev/D-ExpTracker__1023_longmult__0epoch_longmult3dig__v1', 'hyperparameters__rl') # Load stage-specific logs sft_logs = load_dataset('TAUR-dev/D-ExpTracker__1023_longmult__0epoch_longmult3dig__v1', 'logs__sft') rl_logs = load_dataset('TAUR-dev/D-ExpTracker__1023_longmult__0epoch_longmult3dig__v1', 'logs__rl') # Load evaluation results with annotations sft_eval_results = load_dataset('TAUR-dev/D-ExpTracker__1023_longmult__0epoch_longmult3dig__v1', 'evals_eval_sft') rl_eval_results = load_dataset('TAUR-dev/D-ExpTracker__1023_longmult__0epoch_longmult3dig__v1', 'evals_eval_rl') ``` ## Models - [TAUR-dev/M-1023_longmult__0epoch_longmult3dig-rl](https://huggingface.co/TAUR-dev/M-1023_longmult__0epoch_longmult3dig-rl) ## Registry All models from this experiment are automatically registered in the [SkillFactory Model Registry](https://huggingface.co/datasets/TAUR-dev/SkillFactory-Registration) 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 - 1023_longmult__0epoch_longmult3dig - {stage_name} - {SFT/RL}` --- *Generated by SkillFactory Experiment Management System* *All artifacts uploaded immediately as stages complete with perfect data provenance*