Method CreateTrainingObject

Namespace

LMKit.TextAnalysis

Assembly

LM-Kit.NET.dll

CreateTrainingObject(TrainingDataset, int, bool, int?)

Creates a training object for fine-tuning a sentiment analysis model using a specified dataset.

public LoraFinetuning CreateTrainingObject(SentimentAnalysis.TrainingDataset dataset, int maxSamples = 2147483647, bool shuffle = false, int? seed = null)

Parameters

dataset SentimentAnalysis.TrainingDataset

The dataset to be used for training.

maxSamples int

The maximum number of samples to use from the dataset. Default is int.MaxValue.

shuffle bool

Indicates whether to shuffle the dataset before selecting samples. Default is false.

seed int?

An optional seed for the random number generator used when shuffling. If null, the shuffle operation will not be seeded.

Returns

LoraFinetuning

A LoraFinetuning object configured with the training data.

Exceptions

ArgumentException

Thrown if the dataset is not recognized.

InvalidModelException

Thrown if fine-tuning is not supported for Embedding classification mode.

CreateTrainingObject(IList<(string, SentimentCategory)>, int)

Creates an object for fine-tuning a sentiment analysis model using the provided training data.

public LoraFinetuning CreateTrainingObject(IList<(string, SentimentAnalysis.SentimentCategory)> trainingData, int maxSamples = 2147483647)

Parameters

trainingData IList<(string, SentimentAnalysis.SentimentCategory)>

A list of tuples where each tuple contains a text (string) and its corresponding sentiment category (SentimentCategory).
The text represents the input data, and the sentiment category represents the expected output.

maxSamples int

The maximum number of training samples to use. The default value is int.MaxValue. If the number of samples in trainingData exceeds this value, only the first maxSamples samples will be used.

Returns

LoraFinetuning

A LoraFinetuning object configured for fine-tuning the sentiment analysis model with the provided training data.

Exceptions

ArgumentNullException

Thrown if the trainingData argument is null.

ArgumentException

Thrown if the trainingData list is empty, or if any entry in the list is associated with an undefined sentiment category.

InvalidModelException

Thrown if fine-tuning is not supported for Embedding classification mode.