bert-base-banking77-pt2

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bert-base-banking77-pt2

This model is a fine-tuned version of bert-base-uncased on an PolyAI/banking77 dataset. It achieves the following results on the evaluation set:

• Loss: 0.3089
• F1: 0.9362

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 32
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Framework versions

• Transformers 4.42.4
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1

How to use

from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline

ckpt = 'sharmax-vikas/bert-base-banking77-pt2'
tokenizer = AutoTokenizer.from_pretrained(ckpt)
model = AutoModelForSequenceClassification.from_pretrained(ckpt)

classifier = pipeline('text-classification', tokenizer=tokenizer, model=model)
classifier('What is the base of the exchange rates?')
# Output: [{'label': 'exchange_rate', 'score': 0.9961327314376831}]