gastos-bancarios-classifier

Spanish Bank Transaction Classifier

Fine-tuned dccuchile/bert-base-spanish-wwm-cased to classify Spanish bank transaction descriptions into 14 spending categories.

Test accuracy: 86.4%

Motivation

I built a personal finance app and wanted automatic transaction categorization. The tricky part wasn't the model — it was the data. Real bank statements are messy: truncated merchant names, mixed case, reference codes, and genuinely ambiguous transactions (COMPRA AMAZON could be anything).

Dataset

Rather than scraping real transactions, I generated a synthetic dataset of 1,400 examples designed to be hard to classify. The key constraints:

• Realistic formatting — descriptions follow actual bank statement patterns (COMPRA MERCADONA, CARGO PERIODICO NETFLIX, TPV ZARA MAD)
• Deliberate ambiguity — the same merchant appears under different categories depending on context (NIKE → Ropa or Deporte, CARREFOUR → Alimentacion or Tecnologia)
• Imbalanced classes — reflects real spending distributions, not artificial balance
• Noisy examples — truncated strings, mixed case, embedded dates, Bizum transfers with no useful description

Dataset: marinamen/gastos-bancarios-es

Categories

Alimentacion · Restaurantes · Transporte · Ropa · Salud · Tecnologia · Hogar · Viajes · Educacion · Deporte · Entretenimiento · Energia · Alquiler · Varios

Training

model = "dccuchile/bert-base-spanish-wwm-cased"
epochs = 15
learning_rate = 3e-5
batch_size = 16
max_length = 64

Chose Spanish BERT over multilingual DistilBERT after the multilingual model stalled at 42% — the Spanish-specific pretraining made a significant difference on short, noisy text.

Results

Entretenimiento is the weakest category — it overlaps with Tecnologia on merchants like Apple and Amazon, which is expected given how those companies operate.

Usage

from transformers import pipeline

classifier = pipeline("text-classification", model="marinamen/gastos-bancarios-classifier")
classifier("CARGO PERIODICO NETFLIX")
# [{'label': 'Entretenimiento', 'score': 0.97}]

Try it

Interactive demo: gastos-bancarios-space