| language: en | |
| license: mit | |
| # Model Card | |
| Bank Product Classifier - distilBERT | |
| Developed by: Richard Chai, https://www.linkedin.com/in/richardchai/ | |
| This model has been fine-tuned for Bank Product Identification. | |
| Currently, it identifies the following products: | |
| ['account', | |
| 'atm', | |
| 'card', | |
| 'credit_card', | |
| 'current_account', | |
| 'debit_card', | |
| 'fixed_deposit', | |
| 'forex_account', | |
| 'loan', | |
| 'mobile_app', | |
| 'others', | |
| 'savings_account', | |
| 'website'] | |
| i | |
| ## Model Details | |
| - **Model type**: Transformer-based (e.g., BERT, DistilBERT, etc.) | |
| - **Dataset**: Stanford Sentiment Treebank SST-5 or another sentiment dataset | |
| - **Fine-tuning**: The model was fine-tuned for X epochs using a learning rate of Y on a dataset with Z samples. | |
| ## Usage | |
| You can use this model to classify text sentiment as follows: | |
| ```python | |
| from transformers import pipeline | |
| model_checkpt = "richardchai/plp_pdt_clr_distilbert" | |
| clf = pipeline('text-classification', model="model_trained/distilbert") | |
| result = clf(['hello, how are you?', "love you", "i am feeling low"]) | |
| print(result) | |
| ``` | |