class MedicalBertForSequenceClassification extends AnnotatorModel[MedicalBertForSequenceClassification] with HasBatchedAnnotate[MedicalBertForSequenceClassification] with WriteTensorflowModel with WriteOnnxModel with HasCaseSensitiveProperties with HasEngine with CheckLicense

MedicalBertForSequenceClassification can load Bert Models with sequence classification/regression head on top (a linear layer on top of the pooled output) e.g. for multi-class document classification tasks.

Pretrained models can be loaded with pretrained of the companion object:

val sequenceClassifier = MedicalBertForSequenceClassification.pretrained()
  .setInputCols("token", "document")
  .setOutputCol("label")

The default model is "bert_sequence_classifier_ade", if no name is provided.

For available pretrained models please see the Models Hub.

Models from the HuggingFace 🤗 Transformers library are also compatible with Spark NLP 🚀. The Spark NLP Workshop example shows how to import them https://github.com/JohnSnowLabs/spark-nlp/discussions/5669.

Example

import spark.implicits._
import com.johnsnowlabs.nlp.base._
import com.johnsnowlabs.nlp.annotator._
import org.apache.spark.ml.Pipeline

val documentAssembler = new DocumentAssembler()
  .setInputCol("text")
  .setOutputCol("document")

val tokenizer = new Tokenizer()
  .setInputCols("document")
  .setOutputCol("token")

val sequenceClassifier = MedicalBertForSequenceClassification.pretrained()
  .setInputCols("token", "document")
  .setOutputCol("label")
  .setCaseSensitive(true)

val pipeline = new Pipeline().setStages(Array(
  documentAssembler,
  tokenizer,
  sequenceClassifier
))

val data = Seq("John Lenon was born in London and lived in Paris. My name is Sarah and I live in London").toDF("text")
val result = pipeline.fit(data).transform(data)

result.select("label.result").show(false)
+--------------------+
|result              |
+--------------------+
|[True, False]       |
+--------------------+
See also

MedicalBertForSequenceClassification for sequnece-level classification

Annotators Main Page for a list of transformer based classifiers

Linear Supertypes
CheckLicense, HasEngine, HasCaseSensitiveProperties, WriteOnnxModel, WriteTensorflowModel, HasBatchedAnnotate[MedicalBertForSequenceClassification], AnnotatorModel[MedicalBertForSequenceClassification], CanBeLazy, RawAnnotator[MedicalBertForSequenceClassification], HasOutputAnnotationCol, HasInputAnnotationCols, HasOutputAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[MedicalBertForSequenceClassification], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
Known Subclasses
ZeroShotRelationExtractionModel, FinanceBertForSequenceClassification, ZeroShotRelationExtractionModel, LegalBertForSequenceClassification, ZeroShotRelationExtractionModel
Ordering
  1. Grouped
  2. Alphabetic
  3. By Inheritance
Inherited
  1. MedicalBertForSequenceClassification
  2. CheckLicense
  3. HasEngine
  4. HasCaseSensitiveProperties
  5. WriteOnnxModel
  6. WriteTensorflowModel
  7. HasBatchedAnnotate
  8. AnnotatorModel
  9. CanBeLazy
  10. RawAnnotator
  11. HasOutputAnnotationCol
  12. HasInputAnnotationCols
  13. HasOutputAnnotatorType
  14. ParamsAndFeaturesWritable
  15. HasFeatures
  16. DefaultParamsWritable
  17. MLWritable
  18. Model
  19. Transformer
  20. PipelineStage
  21. Logging
  22. Params
  23. Serializable
  24. Serializable
  25. Identifiable
  26. AnyRef
  27. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new MedicalBertForSequenceClassification()

    Annotator reference id.

    Annotator reference id. Used to identify elements in metadata or to refer to this annotator type

  2. new MedicalBertForSequenceClassification(uid: String)

    uid

    required uid for storing annotator to disk

Type Members

  1. type AnnotationContent = Seq[Row]
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  2. type AnnotatorType = String
    Definition Classes
    HasOutputAnnotatorType

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T
    Attributes
    protected
    Definition Classes
    Params
  4. def $$[T](feature: StructFeature[T]): T
    Attributes
    protected
    Definition Classes
    HasFeatures
  5. def $$[K, V](feature: MapFeature[K, V]): Map[K, V]
    Attributes
    protected
    Definition Classes
    HasFeatures
  6. def $$[T](feature: SetFeature[T]): Set[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  7. def $$[T](feature: ArrayFeature[T]): Array[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  8. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  9. def _transform(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  10. def afterAnnotate(dataset: DataFrame): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  11. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  12. def batchAnnotate(batchedAnnotations: Seq[Array[Annotation]]): Seq[Seq[Annotation]]

    takes a document and annotations and produces new annotations of this annotator's annotation type

    takes a document and annotations and produces new annotations of this annotator's annotation type

    batchedAnnotations

    Annotations that correspond to inputAnnotationCols generated by previous annotators if any

    returns

    any number of annotations processed for every input annotation. Not necessary one to one relationship

    Definition Classes
    MedicalBertForSequenceClassification → HasBatchedAnnotate
  13. def batchProcess(rows: Iterator[_]): Iterator[Row]
    Definition Classes
    HasBatchedAnnotate
  14. val batchSize: IntParam
    Definition Classes
    HasBatchedAnnotate
  15. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
    Attributes
    protected
    Definition Classes
    MedicalBertForSequenceClassification → AnnotatorModel
  16. val caseSensitive: BooleanParam
    Definition Classes
    HasCaseSensitiveProperties
  17. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  18. def checkValidEnvironment(spark: Option[SparkSession], scopes: Seq[String]): Unit
    Definition Classes
    CheckLicense
  19. def checkValidScope(scope: String): Unit
    Definition Classes
    CheckLicense
  20. def checkValidScopeAndEnvironment(scope: String, spark: Option[SparkSession], checkLp: Boolean): Unit
    Definition Classes
    CheckLicense
  21. def checkValidScopesAndEnvironment(scopes: Seq[String], spark: Option[SparkSession], checkLp: Boolean): Unit
    Definition Classes
    CheckLicense
  22. final def clear(param: Param[_]): MedicalBertForSequenceClassification.this.type
    Definition Classes
    Params
  23. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  24. val coalesceSentences: BooleanParam

    Instead of 1 class per sentence (if inputCols is sentence) output 1 class per document by averaging probabilities in all sentences.

    Instead of 1 class per sentence (if inputCols is sentence) output 1 class per document by averaging probabilities in all sentences. Due to max sequence length limit in almost all transformer models such as BERT (512 tokens), this parameter helps feeding all the sentences into the model and averaging all the probabilities for the entire document instead of probabilities per sentence. (Default: false)

  25. val configProtoBytes: IntArrayParam

    ConfigProto from tensorflow, serialized into byte array.

    ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString()

  26. def copy(extra: ParamMap): MedicalBertForSequenceClassification
    Definition Classes
    RawAnnotator → Model → Transformer → PipelineStage → Params
  27. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  28. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  29. val engine: Param[String]
    Definition Classes
    HasEngine
  30. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  31. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  32. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  33. def explainParams(): String
    Definition Classes
    Params
  34. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  35. def extraValidateMsg: String
    Attributes
    protected
    Definition Classes
    RawAnnotator
  36. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  37. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  38. val features: ArrayBuffer[Feature[_, _, _]]
    Definition Classes
    HasFeatures
  39. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  40. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  41. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  42. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  43. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  44. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  45. def getBatchSize: Int
    Definition Classes
    HasBatchedAnnotate
  46. def getCaseSensitive: Boolean
    Definition Classes
    HasCaseSensitiveProperties
  47. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  48. def getClasses: Array[String]

    Returns labels used to train this model

  49. def getCoalesceSentences: Boolean

  50. def getConfigProtoBytes: Option[Array[Byte]]

  51. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  52. def getEngine: String
    Definition Classes
    HasEngine
  53. def getInputCols: Array[String]
    Definition Classes
    HasInputAnnotationCols
  54. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  55. def getLicenseScopes: Seq[String]
    Attributes
    protected
  56. def getMaxSentenceLength: Int

  57. def getModelIfNotSet: MedicalBertClassification

  58. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  59. final def getOutputCol: String
    Definition Classes
    HasOutputAnnotationCol
  60. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  61. def getSignatures: Option[Map[String, String]]

  62. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  63. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  64. def hasParent: Boolean
    Definition Classes
    Model
  65. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  66. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  67. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  68. val inputAnnotatorTypes: Array[String]

    Input Annotator Types: DOCUMENT, TOKEN

    Input Annotator Types: DOCUMENT, TOKEN

    Definition Classes
    MedicalBertForSequenceClassification → HasInputAnnotationCols
  69. final val inputCols: StringArrayParam
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  70. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  71. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  72. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  73. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  74. val labels: MapFeature[String, Int]

    Labels used to decode predicted IDs back to string tags

  75. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  76. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  77. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  78. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  79. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  80. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  81. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  82. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  83. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  84. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  85. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  86. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  87. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  88. val maxSentenceLength: IntParam

    Max sentence length to process (Default: 128)

  89. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  90. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  91. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  92. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  93. def onWrite(path: String, spark: SparkSession): Unit
    Definition Classes
    MedicalBertForSequenceClassification → ParamsAndFeaturesWritable
  94. val optionalInputAnnotatorTypes: Array[String]
    Definition Classes
    HasInputAnnotationCols
  95. val outputAnnotatorType: AnnotatorType

    Output Annotator Types: CATEGORY

    Output Annotator Types: CATEGORY

    Definition Classes
    MedicalBertForSequenceClassification → HasOutputAnnotatorType
  96. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  97. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  98. var parent: Estimator[MedicalBertForSequenceClassification]
    Definition Classes
    Model
  99. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  100. def sentenceEndTokenId: Int

  101. def sentenceStartTokenId: Int

  102. def set[T](feature: StructFeature[T], value: T): MedicalBertForSequenceClassification.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  103. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): MedicalBertForSequenceClassification.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  104. def set[T](feature: SetFeature[T], value: Set[T]): MedicalBertForSequenceClassification.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  105. def set[T](feature: ArrayFeature[T], value: Array[T]): MedicalBertForSequenceClassification.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  106. final def set(paramPair: ParamPair[_]): MedicalBertForSequenceClassification.this.type
    Attributes
    protected
    Definition Classes
    Params
  107. final def set(param: String, value: Any): MedicalBertForSequenceClassification.this.type
    Attributes
    protected
    Definition Classes
    Params
  108. final def set[T](param: Param[T], value: T): MedicalBertForSequenceClassification.this.type
    Definition Classes
    Params
  109. def setBatchSize(size: Int): MedicalBertForSequenceClassification.this.type
    Definition Classes
    HasBatchedAnnotate
  110. def setCaseSensitive(value: Boolean): MedicalBertForSequenceClassification.this.type
    Definition Classes
    HasCaseSensitiveProperties
  111. def setCoalesceSentences(value: Boolean): MedicalBertForSequenceClassification.this.type

  112. def setConfigProtoBytes(bytes: Array[Int]): MedicalBertForSequenceClassification.this.type

  113. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): MedicalBertForSequenceClassification.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  114. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): MedicalBertForSequenceClassification.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  115. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): MedicalBertForSequenceClassification.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  116. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): MedicalBertForSequenceClassification.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  117. final def setDefault(paramPairs: ParamPair[_]*): MedicalBertForSequenceClassification.this.type
    Attributes
    protected
    Definition Classes
    Params
  118. final def setDefault[T](param: Param[T], value: T): MedicalBertForSequenceClassification.this.type
    Attributes
    protected[org.apache.spark.ml]
    Definition Classes
    Params
  119. final def setInputCols(value: String*): MedicalBertForSequenceClassification.this.type
    Definition Classes
    HasInputAnnotationCols
  120. def setInputCols(value: Array[String]): MedicalBertForSequenceClassification.this.type
    Definition Classes
    HasInputAnnotationCols
  121. def setLabels(value: Map[String, Int]): MedicalBertForSequenceClassification.this.type

  122. def setLazyAnnotator(value: Boolean): MedicalBertForSequenceClassification.this.type
    Definition Classes
    CanBeLazy
  123. def setMaxSentenceLength(value: Int): MedicalBertForSequenceClassification.this.type

  124. def setModelIfNotSet(spark: SparkSession, onnxWrapper: OnnxWrapper, sentenceSeparator: Option[String]): MedicalBertForSequenceClassification.this.type
  125. def setModelIfNotSet(spark: SparkSession, tensorflowWrapper: TensorflowWrapper, sentenceSeparator: Option[String] = None): MedicalBertForSequenceClassification.this.type

  126. final def setOutputCol(value: String): MedicalBertForSequenceClassification.this.type
    Definition Classes
    HasOutputAnnotationCol
  127. def setParent(parent: Estimator[MedicalBertForSequenceClassification]): MedicalBertForSequenceClassification
    Definition Classes
    Model
  128. def setSignatures(value: Map[String, String]): MedicalBertForSequenceClassification.this.type

  129. def setVocabulary(value: Map[String, Int]): MedicalBertForSequenceClassification.this.type

  130. val signatures: MapFeature[String, String]

    It contains TF model signatures for the laded saved model

  131. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  132. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  133. final def transform(dataset: Dataset[_]): DataFrame
    Definition Classes
    AnnotatorModel → Transformer
  134. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  135. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  136. final def transformSchema(schema: StructType): StructType
    Definition Classes
    RawAnnotator → PipelineStage
  137. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  138. val uid: String
    Definition Classes
    MedicalBertForSequenceClassification → Identifiable
  139. def validate(schema: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  140. val vocabulary: MapFeature[String, Int]

    Vocabulary used to encode the words to ids with WordPieceEncoder

  141. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  142. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  143. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  144. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  145. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable
  146. def writeOnnxModel(path: String, spark: SparkSession, onnxWrapper: OnnxWrapper, suffix: String, fileName: String): Unit
    Definition Classes
    WriteOnnxModel
  147. def writeOnnxModels(path: String, spark: SparkSession, onnxWrappersWithNames: Seq[(OnnxWrapper, String)], suffix: String): Unit
    Definition Classes
    WriteOnnxModel
  148. def writeTensorflowHub(path: String, tfPath: String, spark: SparkSession, suffix: String): Unit
    Definition Classes
    WriteTensorflowModel
  149. def writeTensorflowModel(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]]): Unit
    Definition Classes
    WriteTensorflowModel
  150. def writeTensorflowModelV2(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]], savedSignatures: Option[Map[String, String]]): Unit
    Definition Classes
    WriteTensorflowModel

Inherited from CheckLicense

Inherited from HasEngine

Inherited from HasCaseSensitiveProperties

Inherited from WriteOnnxModel

Inherited from WriteTensorflowModel

Inherited from HasBatchedAnnotate[MedicalBertForSequenceClassification]

Inherited from AnnotatorModel[MedicalBertForSequenceClassification]

Inherited from CanBeLazy

Inherited from RawAnnotator[MedicalBertForSequenceClassification]

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[MedicalBertForSequenceClassification]

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Parameters

A list of (hyper-)parameter keys this annotator can take. Users can set and get the parameter values through setters and getters, respectively.

Annotator types

Required input and expected output annotator types

Members

Parameter setters

Parameter getters