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-mix-sentiment is a Arabic model originally trained by CAMeL-Lab.

Predicted Entities

positive, neutral, negative

Live Demo Open in Colab Download Copy S3 URI

How to use

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

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

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

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

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

result = pipeline.fit(data).transform(data)

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

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

val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_mix_sentiment","ar")
    .setInputCols(Array("document", "token"))
    .setOutputCol("ner")

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

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

val result = pipeline.fit(data).transform(data)

Model Information

References

• https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix-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
• https://github.com/CAMeL-Lab/camel_tools