English BertForSequenceClassification Cased model (from philschmid)

Description

Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. BERT-Banking77 is a English model originally trained by philschmid.

Predicted Entities

get_disposable_virtual_card, declined_card_payment, fiat_currency_support, apple_pay_or_google_pay, atm_support, failed_transfer, Refund_not_showing_up, wrong_amount_of_cash_received, getting_virtual_card, verify_my_identity, top_up_by_cash_or_cheque, top_up_by_bank_transfer_charge, balance_not_updated_after_cheque_or_cash_deposit, visa_or_mastercard, cash_withdrawal_charge, pending_top_up, country_support, contactless_not_working, transfer_not_received_by_recipient, card_arrival, top_up_failed, balance_not_updated_after_bank_transfer, topping_up_by_card, card_acceptance, order_physical_card, pending_card_payment, exchange_charge, extra_charge_on_statement, verify_top_up, card_swallowed, card_delivery_estimate, top_up_by_card_charge, exchange_rate, activate_my_card, card_payment_wrong_exchange_rate, passcode_forgotten, supported_cards_and_currencies, why_verify_identity, verify_source_of_funds, card_payment_fee_charged, change_pin, top_up_reverted, virtual_card_not_working, declined_cash_withdrawal, reverted_card_payment?, transfer_fee_charged, card_payment_not_recognised, card_not_working, beneficiary_not_allowed, exchange_via_app, automatic_top_up, lost_or_stolen_card, card_about_to_expire, pin_blocked, card_linking, direct_debit_payment_not_recognised, compromised_card, request_refund, wrong_exchange_rate_for_cash_withdrawal, transfer_into_account, declined_transfer, cash_withdrawal_not_recognised, get_physical_card, edit_personal_details, unable_to_verify_identity, terminate_account, transfer_timing, top_up_limits, pending_cash_withdrawal, disposable_card_limits, getting_spare_card, lost_or_stolen_phone, pending_transfer, receiving_money, cancel_transfer, age_limit, transaction_charged_twice

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_banking77","en") \
    .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_banking77","en")
    .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

References

• https://huggingface.co/philschmid/BERT-Banking77
• https://paperswithcode.com/sota?task=Text+Classification&dataset=BANKING77