TorchSharpCatalog.QuestionAnswer Method
Important
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| QuestionAnswer(MulticlassClassificationCatalog+MulticlassClassificationTrainers, QATrainer+Options) |
Fine tune a ROBERTA model for Question and Answer. The limit for any sentence is 512 tokens. Each word typically will map to a single token, and we automatically add 2 specical tokens (a start token and a separator token) so in general this limit will be 510 words for all sentences. |
| QuestionAnswer(MulticlassClassificationCatalog+MulticlassClassificationTrainers, String, String, String, String, String, String, Int32, Int32, Int32, BertArchitecture, IDataView) |
Fine tune a ROBERTA model for Question and Answer. The limit for any sentence is 512 tokens. Each word typically will map to a single token, and we automatically add 2 specical tokens (a start token and a separator token) so in general this limit will be 510 words for all sentences. |
- Source:
- TorchSharpCatalog.cs
- Source:
- TorchSharpCatalog.cs
- Source:
- TorchSharpCatalog.cs
Fine tune a ROBERTA model for Question and Answer. The limit for any sentence is 512 tokens. Each word typically will map to a single token, and we automatically add 2 specical tokens (a start token and a separator token) so in general this limit will be 510 words for all sentences.
public static Microsoft.ML.TorchSharp.Roberta.QATrainer QuestionAnswer(this Microsoft.ML.MulticlassClassificationCatalog.MulticlassClassificationTrainers catalog, Microsoft.ML.TorchSharp.Roberta.QATrainer.Options options);static member QuestionAnswer : Microsoft.ML.MulticlassClassificationCatalog.MulticlassClassificationTrainers * Microsoft.ML.TorchSharp.Roberta.QATrainer.Options -> Microsoft.ML.TorchSharp.Roberta.QATrainer<Extension()>
Public Function QuestionAnswer (catalog As MulticlassClassificationCatalog.MulticlassClassificationTrainers, options As QATrainer.Options) As QATrainerParameters
The transform's catalog.
- options
- QATrainer.Options
The options for QA.
Returns
Applies to
ML.NET Preview and other versions
| Product | Versions |
|---|---|
| ML.NET | 3.0.0, 4.0.0, Preview |
QuestionAnswer(MulticlassClassificationCatalog+MulticlassClassificationTrainers, String, String, String, String, String, String, Int32, Int32, Int32, BertArchitecture, IDataView)
- Source:
- TorchSharpCatalog.cs
- Source:
- TorchSharpCatalog.cs
- Source:
- TorchSharpCatalog.cs
Fine tune a ROBERTA model for Question and Answer. The limit for any sentence is 512 tokens. Each word typically will map to a single token, and we automatically add 2 specical tokens (a start token and a separator token) so in general this limit will be 510 words for all sentences.
public static Microsoft.ML.TorchSharp.Roberta.QATrainer QuestionAnswer(this Microsoft.ML.MulticlassClassificationCatalog.MulticlassClassificationTrainers catalog, string contextColumnName = "Context", string questionColumnName = "Question", string trainingAnswerColumnName = "TrainingAnswer", string answerIndexColumnName = "AnswerIndex", string predictedAnswerColumnName = "Answer", string scoreColumnName = "Score", int topK = 3, int batchSize = 4, int maxEpochs = 10, Microsoft.ML.TorchSharp.NasBert.BertArchitecture architecture = Microsoft.ML.TorchSharp.NasBert.BertArchitecture.Roberta, Microsoft.ML.IDataView validationSet = default);static member QuestionAnswer : Microsoft.ML.MulticlassClassificationCatalog.MulticlassClassificationTrainers * string * string * string * string * string * string * int * int * int * Microsoft.ML.TorchSharp.NasBert.BertArchitecture * Microsoft.ML.IDataView -> Microsoft.ML.TorchSharp.Roberta.QATrainer<Extension()>
Public Function QuestionAnswer (catalog As MulticlassClassificationCatalog.MulticlassClassificationTrainers, Optional contextColumnName As String = "Context", Optional questionColumnName As String = "Question", Optional trainingAnswerColumnName As String = "TrainingAnswer", Optional answerIndexColumnName As String = "AnswerIndex", Optional predictedAnswerColumnName As String = "Answer", Optional scoreColumnName As String = "Score", Optional topK As Integer = 3, Optional batchSize As Integer = 4, Optional maxEpochs As Integer = 10, Optional architecture As BertArchitecture = Microsoft.ML.TorchSharp.NasBert.BertArchitecture.Roberta, Optional validationSet As IDataView = Nothing) As QATrainerParameters
The transform's catalog.
- contextColumnName
- String
The context for the question.
- questionColumnName
- String
The question being asked.
- trainingAnswerColumnName
- String
The answer used to train the model.
- answerIndexColumnName
- String
The starting character index of that answer in the context.
- predictedAnswerColumnName
- String
The answer predicted by the model during inferencing.
- scoreColumnName
- String
The score of the predicted answers.
- topK
- Int32
How many top results you want back for a given question.
- batchSize
- Int32
Number of rows in the batch.
- maxEpochs
- Int32
Maximum number of times to loop through your training set.
- architecture
- BertArchitecture
Architecture for the model. Defaults to Roberta.
- validationSet
- IDataView
The validation set used while training to improve model quality.
Returns
Applies to
ML.NET Preview and other versions
| Product | Versions |
|---|---|
| ML.NET | 3.0.0, 4.0.0, Preview |