English RobertaForSequenceClassification Cased model (from philschmid)

Description

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

Predicted Entities

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

Live Demo Open in Colab Download Copy S3 URI

How to use

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

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

seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_banking77","en") \
    .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 = RoBertaForSequenceClassification.pretrained("roberta_classifier_banking77","en")
    .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("en.classify.roberta.banking.").predict("""PUT YOUR STRING HERE""")

Model Information

References

References

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