BERT-BankingClassifier
This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2867
- Accuracy: 0.9326
Model description
This model is a BERT (bert-base-uncased) model fine-tuned using the Banking77 dataset for text classification tasks. Banking77 is a dataset designed to categorize customer support messages in the banking and finance domain into 77 distinct categories. This model is specifically tailored for classifying customer complaints and inquiries in the banking sector, helping to assign messages to the correct categories effectively. Fine-Tuning Process : https://github.com/saribasmetehan/bank_administrative_assistant/blob/main/BERT_BankingClassifier.ipynb
Label Index | Intent Category |
---|---|
0 | activate_my_card |
1 | age_limit |
2 | apple_pay_or_google_pay |
3 | atm_support |
4 | automatic_top_up |
5 | balance_not_updated_after_bank_transfer |
6 | balance_not_updated_after_cheque_or_cash_deposit |
7 | beneficiary_not_allowed |
8 | cancel_transfer |
9 | card_about_to_expire |
10 | card_acceptance |
11 | card_arrival |
12 | card_delivery_estimate |
13 | card_linking |
14 | card_not_working |
15 | card_payment_fee_charged |
16 | card_payment_not_recognised |
17 | card_payment_wrong_exchange_rate |
18 | card_swallowed |
19 | cash_withdrawal_charge |
20 | cash_withdrawal_not_recognised |
21 | change_pin |
22 | compromised_card |
23 | contactless_not_working |
24 | country_support |
25 | declined_card_payment |
26 | declined_cash_withdrawal |
27 | declined_transfer |
28 | direct_debit_payment_not_recognised |
29 | disposable_card_limits |
30 | edit_personal_details |
31 | exchange_charge |
32 | exchange_rate |
33 | exchange_via_app |
34 | extra_charge_on_statement |
35 | failed_transfer |
36 | fiat_currency_support |
37 | get_disposable_virtual_card |
38 | get_physical_card |
39 | getting_spare_card |
40 | getting_virtual_card |
41 | lost_or_stolen_card |
42 | lost_or_stolen_phone |
43 | order_physical_card |
44 | passcode_forgotten |
45 | pending_card_payment |
46 | pending_cash_withdrawal |
47 | pending_top_up |
48 | pending_transfer |
49 | pin_blocked |
50 | receiving_money |
51 | refund_not_showing_up |
52 | request_refund |
53 | reverted_card_payment |
54 | supported_cards_and_currencies |
55 | terminate_account |
56 | top_up_by_bank_transfer_charge |
57 | top_up_by_card_charge |
58 | top_up_by_cash_or_cheque |
59 | top_up_failed |
60 | top_up_limits |
61 | top_up_reverted |
62 | topping_up_by_card |
63 | transaction_charged_twice |
64 | transfer_fee_charged |
65 | transfer_into_account |
66 | transfer_not_received_by_recipient |
67 | transfer_timing |
68 | unable_to_verify_identity |
69 | verify_my_identity |
70 | verify_source_of_funds |
71 | verify_top_up |
72 | virtual_card_not_working |
73 | visa_or_mastercard |
74 | why_verify_identity |
75 | wrong_amount_of_cash_received |
76 | wrong_exchange_rate_for_cash_withdrawal |
Example
from transformers import pipeline, AutoTokenizer
text = "i forgot my PIN"
model_id = "saribasmetehan/BERT-BankingClassifier"
classifier = pipeline("text-classification", model=model_id)
preds = classifier(text)
print(preds)
#[{'label': 'LABEL_27', 'score': 0.9552194476127625}]
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
2.5368 | 1.0 | 732 | 0.5945 | 0.8862 |
0.6013 | 2.0 | 1464 | 0.3156 | 0.9283 |
0.1507 | 3.0 | 2196 | 0.2895 | 0.9290 |
0.089 | 4.0 | 2928 | 0.2867 | 0.9326 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for saribasmetehan/BERT-BankingClassifier
Base model
google-bert/bert-base-uncased