richardchai/plp_pdt_clr_tinybert

Model Card

Bank Product Classifier - TinyBert 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']

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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:

from transformers import pipeline

model_checkpt = "richardchai/plp_pdt_clr_tinybert"
clf = pipeline('text-classification', model="model_trained/tinybert")
result = clf(['hello, how are you?', "love you", "i am feeling low"])
print(result)