import * as z from "zod/v4";
import { Result as SafeParseResult } from "../../types/fp.js";
import { SDKValidationError } from "../errors/sdkvalidationerror.js";
export type ClassifierTrainingParameters = {
    /**
     * 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;
};
/** @internal */
export declare const ClassifierTrainingParameters$inboundSchema: z.ZodType<ClassifierTrainingParameters, unknown>;
/** @internal */
export type ClassifierTrainingParameters$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;
};
/** @internal */
export declare const ClassifierTrainingParameters$outboundSchema: z.ZodType<ClassifierTrainingParameters$Outbound, ClassifierTrainingParameters>;
export declare function classifierTrainingParametersToJSON(classifierTrainingParameters: ClassifierTrainingParameters): string;
export declare function classifierTrainingParametersFromJSON(jsonString: string): SafeParseResult<ClassifierTrainingParameters, SDKValidationError>;
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