Create Reinforcement Fine-tuning Job
Authorizations
Bearer authentication using your Fireworks API key. Format: Bearer <API_KEY>
Path Parameters
The Account Id
Query Parameters
ID of the reinforcement fine-tuning job, a random UUID will be generated if not specified.
Body
The name of the dataset used for training.
The evaluator resource name to use for RLOR fine-tuning job.
The name of a separate dataset to use for evaluation.
Whether to auto-carve the dataset for eval.
Common training configurations.
The Weights & Biases team/user account for logging training progress.
The AWS configuration for S3 dataset access.
The Azure configuration for Blob Storage dataset access.
RFT inference parameters.
Data chunking for rollout, default size 200, enabled when dataset > 300. Valid range is 1-10,000.
The number of nodes to use for the fine-tuning job. If not specified, the default is 1.
Reinforcement learning loss method + hyperparameters for the underlying trainers.
Maximum number of concurrent rollouts during the RFT job.
Maximum number of concurrent evaluations during the RFT job.
Scheduling purpose for this job.
PURPOSE_UNSPECIFIED, PURPOSE_PILOT Response
A successful response.
The name of the dataset used for training.
The evaluator resource name to use for RLOR fine-tuning job.
The completed time for the reinforcement fine-tuning job.
The name of a separate dataset to use for evaluation.
Whether to auto-carve the dataset for eval.
JobState represents the state an asynchronous job can be in.
- JOB_STATE_PAUSED: Job is paused, typically due to account suspension or manual intervention.
- JOB_STATE_DELETED: Job has been deleted.
JOB_STATE_UNSPECIFIED, JOB_STATE_CREATING, JOB_STATE_RUNNING, JOB_STATE_COMPLETED, JOB_STATE_FAILED, JOB_STATE_CANCELLED, JOB_STATE_DELETING, JOB_STATE_WRITING_RESULTS, JOB_STATE_VALIDATING, JOB_STATE_DELETING_CLEANING_UP, JOB_STATE_PENDING, JOB_STATE_EXPIRED, JOB_STATE_RE_QUEUEING, JOB_STATE_CREATING_INPUT_DATASET, JOB_STATE_IDLE, JOB_STATE_CANCELLING, JOB_STATE_EARLY_STOPPED, JOB_STATE_PAUSED, JOB_STATE_DELETED The email address of the user who initiated this fine-tuning job.
Common training configurations.
The Weights & Biases team/user account for logging training progress.
The AWS configuration for S3 dataset access.
The Azure configuration for Blob Storage dataset access.
The output dataset's aggregated stats for the evaluation job.
Job progress.
RFT inference parameters.
Data chunking for rollout, default size 200, enabled when dataset > 300. Valid range is 1-10,000.
The number of nodes to use for the fine-tuning job. If not specified, the default is 1.
Reinforcement learning loss method + hyperparameters for the underlying trainers.
The signed URL for the trainer logs file (stdout/stderr). Only populated if the account has trainer log reading enabled.
Accelerator seconds used by the job, keyed by accelerator type (e.g., "NVIDIA_H100_80GB"). Updated when job completes or is cancelled.
Maximum number of concurrent rollouts during the RFT job.
Maximum number of concurrent evaluations during the RFT job.
Scheduling purpose for this job.
PURPOSE_UNSPECIFIED, PURPOSE_PILOT