bert-base-banking77-pt2

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.3111
• F1: 0.9275

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: 16
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	F1
1.0958	1.0	626	0.7854	0.8363
0.3958	2.0	1252	0.3744	0.9168
0.1894	3.0	1878	0.3111	0.9275

Framework versions

• Transformers 4.27.1
• Pytorch 2.4.1+cu121
• Datasets 2.9.0
• Tokenizers 0.13.3

How to use

from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline

ckpt = 'pistachio7/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}]