Arabic BertForSequenceClassification Base Cased model (from CAMeL-Lab)

Description

Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. bert-base-arabic-camelbert-ca-sentiment is a Arabic model originally trained by CAMeL-Lab.

Predicted Entities

negative, neutral, positive

Download Copy S3 URI

How to use

documentAssembler = DocumentAssembler() \
    .setInputCol("text") \
    .setOutputCol("document")

tokenizer = Tokenizer() \
    .setInputCols("document") \
    .setOutputCol("token")

seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bert_base_arabic_camelbert_ca_sentiment","ar") \
    .setInputCols(["document", "token"]) \
    .setOutputCol("class")

pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier])

data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")

result = pipeline.fit(data).transform(data)
val documentAssembler = new DocumentAssembler()
      .setInputCols(Array("text"))
      .setOutputCols(Array("document"))

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

val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bert_base_arabic_camelbert_ca_sentiment","ar")
    .setInputCols(Array("document", "token"))
    .setOutputCol("class")

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

val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")

val result = pipeline.fit(data).transform(data)
import nlu
nlu.load("ar.classify.bert.sentiment.base").predict("""PUT YOUR STRING HERE""")

Model Information

Model Name: bert_classifier_bert_base_arabic_camelbert_ca_sentiment
Compatibility: Spark NLP 4.1.0+
License: Open Source
Edition: Official
Input Labels: [document, token]
Output Labels: [class]
Language: ar
Size: 409.5 MB
Case sensitive: true
Max sentence length: 256

References

  • https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-ca-sentiment
  • https://aclanthology.org/D15-1299.pdf
  • http://lrec-conf.org/workshops/lrec2018/W30/pdf/22_W30.pdf
  • https://aclanthology.org/S17-2088.pdf
  • https://arxiv.org/abs/2103.06678
  • https://github.com/CAMeL-Lab/CAMeLBERT
  • https://github.com/CAMeL-Lab/camel_tools