import * as z from "zod/v3";
/**
 * The fine-tuning hyperparameter settings used in a fine-tune job.
 */
export type CompletionTrainingParametersIn = {
    /**
     * The number of training steps to perform. A training step refers to a single update of the model weights during the fine-tuning process. This update is typically calculated using a batch of samples from the training dataset.
     */
    trainingSteps?: number | null | undefined;
    /**
     * A parameter describing how much to adjust the pre-trained model's weights in response to the estimated error each time the weights are updated during the fine-tuning process.
     */
    learningRate?: number | undefined;
    /**
     * (Advanced Usage) Weight decay adds a term to the loss function that is proportional to the sum of the squared weights. This term reduces the magnitude of the weights and prevents them from growing too large.
     */
    weightDecay?: number | null | undefined;
    /**
     * (Advanced Usage) A parameter that specifies the percentage of the total training steps at which the learning rate warm-up phase ends. During this phase, the learning rate gradually increases from a small value to the initial learning rate, helping to stabilize the training process and improve convergence. Similar to `pct_start` in [mistral-finetune](https://github.com/mistralai/mistral-finetune)
     */
    warmupFraction?: number | null | undefined;
    epochs?: number | null | undefined;
    seqLen?: number | null | undefined;
    fimRatio?: number | null | undefined;
};
/** @internal */
export type CompletionTrainingParametersIn$Outbound = {
    training_steps?: number | null | undefined;
    learning_rate: number;
    weight_decay?: number | null | undefined;
    warmup_fraction?: number | null | undefined;
    epochs?: number | null | undefined;
    seq_len?: number | null | undefined;
    fim_ratio?: number | null | undefined;
};
/** @internal */
export declare const CompletionTrainingParametersIn$outboundSchema: z.ZodType<CompletionTrainingParametersIn$Outbound, z.ZodTypeDef, CompletionTrainingParametersIn>;
export declare function completionTrainingParametersInToJSON(completionTrainingParametersIn: CompletionTrainingParametersIn): string;
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