pub struct FineTuningJob {Show 18 fields
pub id: String,
pub created_at: i64,
pub error: Option<Error>,
pub fine_tuned_model: Option<String>,
pub finished_at: Option<i64>,
pub hyperparameters: Hyperparameters,
pub model: String,
pub organization_id: String,
pub result_files: Vec<String>,
pub status: Status,
pub trained_tokens: Option<i64>,
pub training_file: String,
pub validation_file: Option<String>,
pub integrations: Option<Vec<Item>>,
pub seed: i64,
pub estimated_finish: Option<i64>,
pub method: Option<FineTuneMethod>,
pub metadata: Option<Metadata>,
}Expand description
The fine_tuning.job object represents a fine-tuning job that has been created through the API.
Fields§
§id: StringThe object identifier, which can be referenced in the API endpoints.
created_at: i64The Unix timestamp (in seconds) for when the fine-tuning job was created.
error: Option<Error>For fine-tuning jobs that have failed, this will contain more information on the cause of the failure.
fine_tuned_model: Option<String>The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running.
finished_at: Option<i64>The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running.
hyperparameters: HyperparametersThe hyperparameters used for the fine-tuning job. This value will only be returned when running supervised jobs.
model: StringThe base model that is being fine-tuned.
organization_id: StringThe organization that owns the fine-tuning job.
result_files: Vec<String>The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the Files API.
status: StatusThe current status of the fine-tuning job, which can be either validating_files, queued, running, succeeded, failed, or cancelled.
trained_tokens: Option<i64>The total number of billable tokens processed by this fine-tuning job. The value will be null if the fine-tuning job is still running.
training_file: StringThe file ID used for training. You can retrieve the training data with the Files API.
validation_file: Option<String>The file ID used for validation. You can retrieve the validation results with the Files API.
integrations: Option<Vec<Item>>A list of integrations to enable for this fine-tuning job.
seed: i64The seed used for the fine-tuning job.
estimated_finish: Option<i64>The Unix timestamp (in seconds) for when the fine-tuning job is estimated to finish. The value will be null if the fine-tuning job is not running.
method: Option<FineTuneMethod>§metadata: Option<Metadata>Implementations§
Source§impl FineTuningJob
impl FineTuningJob
Sourcepub fn builder() -> FineTuningJobBuilder<((), (), (), (), (), (), (), (), (), (), (), (), (), (), (), (), (), ())>
pub fn builder() -> FineTuningJobBuilder<((), (), (), (), (), (), (), (), (), (), (), (), (), (), (), (), (), ())>
Create a builder for building FineTuningJob.
On the builder, call .id(...), .created_at(...), .error(...)(optional), .fine_tuned_model(...)(optional), .finished_at(...)(optional), .hyperparameters(...)(optional), .model(...), .organization_id(...), .result_files(...), .status(...), .trained_tokens(...)(optional), .training_file(...), .validation_file(...)(optional), .integrations(...)(optional), .seed(...), .estimated_finish(...)(optional), .method(...)(optional), .metadata(...)(optional) to set the values of the fields.
Finally, call .build() to create the instance of FineTuningJob.
Trait Implementations§
Source§impl Clone for FineTuningJob
impl Clone for FineTuningJob
Source§fn clone(&self) -> FineTuningJob
fn clone(&self) -> FineTuningJob
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source. Read more