metadata
language: en
tags:
- transaction-categorization
- distilbert
- finance
- text-classification
datasets:
- mitulshah/transaction-categorization
license: apache-2.0
Transaction Category Classifier - Full Model
This model classifies bank transactions into 10 categories with 98.53% accuracy.
Model Details
- Model: DistilBERT fine-tuned on 80,000 transactions
- Categories: 10 transaction types
- Size: ~268 MB
Performance
| Metric | Value |
|---|---|
| Accuracy | 98.53% |
| Loss | 0.0221 |
| Training Samples | 80,000 |
| Validation Samples | 20,000 |
Categories
- Charity & Donations
- Entertainment & Recreation
- Financial Services
- Food & Dining
- Government & Legal
- Healthcare & Medical
- Income
- Shopping & Retail
- Transportation
- Utilities & Services
How to Use
from transformers import pipeline
classifier = pipeline("text-classification",
model="finmigodeveloper/distilbert-transaction-classifier")
# Test it
transactions = [
"Starbucks coffee",
"Monthly salary deposit",
"Uber ride to airport"
]
for text in transactions:
result = classifier(text)[0]
print(f"{text}: {result['label']} ({result['score']:.2%})")
Training Details
- Epochs: 3
- Batch Size: 64
- Learning Rate: 2e-5
- Optimizer: AdamW