---
tags:
- setfit
- sentence-transformers
- text-classification
- generated_from_setfit_trainer
widget:
- text: What do I do?  My card is broken.
- text: Where should I withdraw money from?
- text: >-
    I can't seem to make a standard bank transfer. I have tried at least five
    times already but none of them are going through. Please tell me what is
    wrong?
- text: What are the currency exchange fees?
- text: I have an unauthorized charge.
metrics:
- accuracy
pipeline_tag: text-classification
library_name: setfit
inference: true
base_model: BAAI/bge-small-en-v1.5
model_name: TinyModels/setfit-banking-intent
license: apache-2.0
language:
- en
---

<div align="center">

<img src="https://capsule-render.vercel.app/api?type=waving&color=gradient&customColorList=6,11,20,24,30&height=220&section=header&text=SetFit%20Banking%20Intent&fontSize=54&fontColor=ffffff&animation=fadeIn&fontAlignY=32&desc=77-Class%20Intent%20Classification%20%E2%80%A2%20Few-Shot%20Learning%20%E2%80%A2%20SetFit&descAlignY=55&descSize=18&descColor=e0d7ff" width="100%"/>

<a href="https://huggingface.co/TinyModels/setfit-banking-intent">
  <img src="https://readme-typing-svg.demolab.com?font=Fira+Code&weight=700&size=24&duration=2800&pause=900&color=A78BFA&center=true&vCenter=true&multiline=true&width=800&height=90&lines=Classify+banking+intents+in+one+line+of+code.;77+classes+%7C+4+samples+per+class+%7C+SetFit+few-shot.;Powered+by+BAAI%2Fbge-small-en-v1.5.;Built+with+%E2%9D%A4%EF%B8%8F+by+TinyModels." alt="Typing SVG" />
</a>

<br/>


![Task](https://img.shields.io/badge/Task-Text%20Classification-6C63FF?style=for-the-badge&logo=huggingface&logoColor=white)
![Library](https://img.shields.io/badge/Library-SetFit%201.2.0-FF6F91?style=for-the-badge&logo=python&logoColor=white)
![Backbone](https://img.shields.io/badge/Backbone-bge--small--en--v1.5-00C2A8?style=for-the-badge&logo=ai&logoColor=white)
![Classes](https://img.shields.io/badge/Classes-77-F7B32B?style=for-the-badge&logo=target&logoColor=white)
![F1](https://img.shields.io/badge/Metric-Accuracy-34D399?style=for-the-badge&logo=checkmarx&logoColor=white)

![Python](https://img.shields.io/badge/Python-3.13-3776AB?style=flat-square&logo=python&logoColor=white)
![PyTorch](https://img.shields.io/badge/PyTorch-2.11-EE4C2C?style=flat-square&logo=pytorch&logoColor=white)
![Transformers](https://img.shields.io/badge/Transformers-5.16-FFD21E?style=flat-square&logo=huggingface&logoColor=black)
![SentenceTransformers](https://img.shields.io/badge/SentenceTransformers-5.7-8A2BE2?style=flat-square&logo=scikitlearn&logoColor=white)
![scikit-learn](https://img.shields.io/badge/scikit--learn-LogReg-F7931E?style=flat-square&logo=scikitlearn&logoColor=white)

![Status](https://img.shields.io/badge/Status-Active-brightgreen?style=flat-square)
![Maintained](https://img.shields.io/badge/Maintained-Yes-success?style=flat-square)
![PRs](https://img.shields.io/badge/PRs-Welcome-blueviolet?style=flat-square)
![License](https://img.shields.io/badge/License-See%20Hub-lightgrey?style=flat-square)

<br/>


<img src="https://media.giphy.com/media/3o7aCTfyhYawdOXcFW/giphy.gif" width="140" alt="animated spark"/>

<br/><br/>

> ### 🏦 A tiny, fast, and accurate **SetFit** classifier that routes banking customer intents — trained with **just 4 examples per class** (308 sentences total).

</div>

<img src="https://user-images.githubusercontent.com/74038190/212284100-561aa473-3905-4a80-b561-0d28506553ee.gif" width="100%">

---


<div align="center">

### 🧭 Table of Contents

<a href="#-model-description"><kbd>📖 Description</kbd></a> &nbsp;•&nbsp;
<a href="#-architecture"><kbd>🏗️ Architecture</kbd></a> &nbsp;•&nbsp;
<a href="#-quick-start"><kbd>🚀 Quick Start</kbd></a> &nbsp;•&nbsp;
<a href="#-model-labels-77-classes"><kbd>🏷️ Labels</kbd></a> &nbsp;•&nbsp;
<a href="#-training-details"><kbd>🎓 Training</kbd></a> &nbsp;•&nbsp;
<a href="#-bias-risks--limitations"><kbd>⚠️ Risks</kbd></a> &nbsp;•&nbsp;
<a href="#-citation"><kbd>📜 Citation</kbd></a>

</div>

---

## 📖 Model Description

<div align="center">

| 🔍 | 💡 |
|:--:|:--|
| **Model Type** | `SetFit` — Efficient Few-Shot Learning |
| **Author** | **[TinyModels](https://huggingface.co/TinyModels)** |
| **Sentence Transformer** | [`BAAI/bge-small-en-v1.5`](https://huggingface.co/BAAI/bge-small-en-v1.5) |
| **Classification Head** | [`sklearn.linear_model.LogisticRegression`](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) |
| **Max Sequence Length** | `512` tokens |
| **Number of Classes** | `77` banking intents |
| **Training Samples** | `4` per class — `308` total |
| **Language** | English 🇬🇧 |
| **Domain** | 🏦 Banking / Fintech customer support |

</div>

### 🌟 Why SetFit?

> SetFit achieves strong accuracy **without prompts and without large labeled datasets**.  
> It first fine-tunes a sentence embedding model with **contrastive learning**, then trains a lightweight classifier on top — perfect for low-data, high-class-count problems like this one.

---

## 🏗️ Architecture

```mermaid
flowchart LR
    A["📝 Input Text<br/>(customer message)"] --> B["🔤 BAAI/bge-small-en-v1.5<br/>Sentence Transformer"]
    B --> C["🧬 Sentence Embedding<br/>(384-dim)"]
    C --> D["🎯 LogisticRegression<br/>Classification Head"]
    D --> E["🏷️ Predicted Intent<br/>(1 of 77 classes)"]

    subgraph TRAIN["🎓 Training Pipeline"]
        direction TB
        T1["Contrastive Fine-tuning<br/>(CosineSimilarityLoss)"] --> T2["Embedding Extraction"]
        T2 --> T3["LogReg Head Training"]
    end

    style A fill:#6C63FF,color:#fff,stroke:#4B4BFF,stroke-width:2px
    style B fill:#FF6F91,color:#fff,stroke:#E0567A,stroke-width:2px
    style C fill:#00C2A8,color:#fff,stroke:#009E88,stroke-width:2px
    style D fill:#F7B32B,color:#000,stroke:#D99A1F,stroke-width:2px
    style E fill:#34D399,color:#000,stroke:#25A67A,stroke-width:2px
    style TRAIN fill:#1a1a2e,color:#fff,stroke:#6C63FF,stroke-dasharray: 5 5
```

<img src="https://user-images.githubusercontent.com/74038190/212284100-561aa473-3905-4a80-b561-0d28506553ee.gif" width="100%">

---

## 🚀 Quick Start

<details open>
<summary><b>🐍 Python — one-liner inference</b></summary>

```bash
pip install setfit
```

```python
from setfit import SetFitModel

# 🔽 Load from the Hub
model = SetFitModel.from_pretrained("TinyModels/setfit-banking-intent")

# 🎯 Run inference
preds = model("I have an unauthorized charge.")
print(preds)
# → ['direct_debit_payment_not_recognised']
```

</details>

<details>
<summary><b>📦 Batch inference with confidence scores</b></summary>

```python
from setfit import SetFitModel
import numpy as np

model = SetFitModel.from_pretrained("TinyModels/setfit-banking-intent")

texts = [
    "What do I do? My card is broken.",
    "Where should I withdraw money from?",
    "What are the currency exchange fees?",
    "I have an unauthorized charge.",
]

# Predicted labels
labels = model(texts)
print(labels)

# Probability distribution per class
probs = model.predict_proba(texts)
top_idx = np.argmax(probs, axis=1)
top_conf = probs[np.arange(len(texts)), top_idx]

for t, l, c in zip(texts, labels, top_conf):
    print(f"[{c:0.2%}] {l:<40} ← {t}")
```

</details>

<details>
<summary><b>⚡ FastAPI microservice snippet</b></summary>

```python
from fastapi import FastAPI
from pydantic import BaseModel
from setfit import SetFitModel

app = FastAPI(title="Banking Intent API")
model = SetFitModel.from_pretrained("TinyModels/setfit-banking-intent")

class Query(BaseModel):
    text: str

@app.post("/classify")
def classify(q: Query):
    label = model([q.text])[0]
    return {"intent": label, "text": q.text}
```

</details>

---

## 🏷️ Model Labels (77 Classes)

<div align="center">

![Classes](https://img.shields.io/badge/Total%20Intents-77-6C63FF?style=for-the-badge)
![Categories](https://img.shields.io/badge/Categories-10-FF6F91?style=for-the-badge)

</div>

<details>
<summary>💳 <b>Card Management</b> — <i>20 classes</i></summary>

| Label | Example Utterance |
|:------|:------------------|
| `activate_my_card` | *I have a new card and need to activate it* |
| `card_about_to_expire` | *Do I need to do something to get a new card once it expires?* |
| `card_acceptance` | *Where can I use my Mastercard?* |
| `card_arrival` | *Where is the card I ordered 2 weeks ago?* |
| `card_delivery_estimate` | *What is the delivery time for US?* |
| `card_linking` | *My new card isn't in my app, how do I get it in there?* |
| `card_not_working` | *What do I do? My card is broken.* |
| `card_swallowed` | *Please send a new card; the ATM ate mine.* |
| `contactless_not_working` | *Why is my contactless not working?* |
| `country_support` | *Will my new card work outside of the EU?* |
| `disposable_card_limits` | *Is there a limit to how many times I can use my disposable virtual card?* |
| `get_disposable_virtual_card` | *Where can I order a disposable virtual card?* |
| `get_physical_card` | *In the app, where do I find my card PIN?* |
| `getting_spare_card` | *Is it possible to get another card?* |
| `getting_virtual_card` | *How do I receive a virtual card?* |
| `lost_or_stolen_card` | *I've lost my card. What can I do about that?* |
| `order_physical_card` | *How do I ask for a physical card?* |
| `supported_cards_and_currencies` | *What currencies are approved to add money?* |
| `virtual_card_not_working` | *Why isn't my disposable virtual card working?* |
| `visa_or_mastercard` | *Which one are you? Visa or Mastercard?* |

</details>

<details>
<summary>💸 <b>Payments</b> — <i>9 classes</i></summary>

| Label | Example Utterance |
|:------|:------------------|
| `apple_pay_or_google_pay` | *How can I get my Google pay top up to work?* |
| `card_payment_fee_charged` | *Why am I getting charged more for using my card?* |
| `card_payment_not_recognised` | *I don't understand where this charge came from.* |
| `card_payment_wrong_exchange_rate` | *My exchange rate isn't correct.* |
| `declined_card_payment` | *You have declined my payment.* |
| `extra_charge_on_statement` | *Why is there a $1 charge on my statement?* |
| `pending_card_payment` | *A card payment on my account is shown as pending.* |
| `reverted_card_payment?` | *I did a payment but it was reverted by the app.* |
| `transaction_charged_twice` | *I have a duplicate charge.* |

</details>

<details>
<summary>🔁 <b>Transfers</b> — <i>12 classes</i></summary>

| Label | Example Utterance |
|:------|:------------------|
| `balance_not_updated_after_bank_transfer` | *I just transferred some money and do not see it updated yet.* |
| `beneficiary_not_allowed` | *Why can't I use my beneficiary?* |
| `cancel_transfer` | *Please cancel the transfer I just made.* |
| `declined_transfer` | *I got a message that my transfer was declined.* |
| `failed_transfer` | *I can't seem to make a standard bank transfer.* |
| `pending_transfer` | *I am still waiting for a transfer to show up.* |
| `receiving_money` | *How can my boss pay me directly to the card?* |
| `transfer_fee_charged` | *Why was I charged a fee for transferring money?* |
| `transfer_into_account` | *How can I transfer money to this account from another bank?* |
| `transfer_not_received_by_recipient` | *I transferred money and it didn't get there.* |
| `transfer_timing` | *How long until transfers from Europe go through?* |
| `top_up_by_bank_transfer_charge` | *If I top up by transfer, am I going to be charged?* |

</details>

<details>
<summary>⬆️ <b>Top-ups</b> — <i>9 classes</i></summary>

| Label | Example Utterance |
|:------|:------------------|
| `automatic_top_up` | *How can I setup automatic top-up?* |
| `pending_top_up` | *Why is the top-up I made still pending?* |
| `top_up_by_card_charge` | *Do you have any fees if I want to add money using an international card?* |
| `top_up_by_cash_or_cheque` | *Can I top up with check?* |
| `top_up_failed` | *I don't think that my top-up worked.* |
| `top_up_limits` | *What's the top-up limit?* |
| `top_up_reverted` | *Why did my top-up get reverted?* |
| `topping_up_by_card` | *I can't see my top up in my wallet!* |
| `verify_top_up` | *How are top-ups verified?* |

</details>

<details>
<summary>🏧 <b>Cash & ATM</b> — <i>8 classes</i></summary>

| Label | Example Utterance |
|:------|:------------------|
| `atm_support` | *Where should I withdraw money from?* |
| `balance_not_updated_after_cheque_or_cash_deposit` | *Why isn't my cash deposit showing up in my account?* |
| `cash_withdrawal_charge` | *I got charged fees for withdrawing cash!* |
| `cash_withdrawal_not_recognised` | *I see cash withdrawals that I did not authorize.* |
| `declined_cash_withdrawal` | *Is my card broken? I can't get cash out of the ATM.* |
| `pending_cash_withdrawal` | *My ATM withdrawal is taking forever.* |
| `wrong_amount_of_cash_received` | *I only got $20 of the $100 that I attempted to withdraw.* |
| `wrong_exchange_rate_for_cash_withdrawal` | *I received the incorrect exchange rate.* |

</details>

<details>
<summary>🔐 <b>Security & PIN</b> — <i>5 classes</i></summary>

| Label | Example Utterance |
|:------|:------------------|
| `change_pin` | *Can you tell me how to change my PIN?* |
| `compromised_card` | *The card has suffered a security breach.* |
| `lost_or_stolen_phone` | *My app was on the phone and I was mugged.* |
| `passcode_forgotten` | *I thought I knew my password but I guess I was wrong.* |
| `pin_blocked` | *Help me unblock my account. I entered the PIN wrong too many times.* |

</details>

<details>
<summary>🪪 <b>Identity Verification</b> — <i>4 classes</i></summary>

| Label | Example Utterance |
|:------|:------------------|
| `unable_to_verify_identity` | *The app is not able to realize that it is me.* |
| `verify_my_identity` | *Can I get information on the identity checks?* |
| `verify_source_of_funds` | *I'd like to know where my funds come from.* |
| `why_verify_identity` | *What is the function of the identity check?* |

</details>

<details>
<summary>👤 <b>Account Management</b> — <i>3 classes</i></summary>

| Label | Example Utterance |
|:------|:------------------|
| `age_limit` | *At what age can a person open an account?* |
| `edit_personal_details` | *I just got married and need to change my name on the account.* |
| `terminate_account` | *How can I delete my account?* |

</details>

<details>
<summary>💱 <b>Fees & Currency</b> — <i>4 classes</i></summary>

| Label | Example Utterance |
|:------|:------------------|
| `exchange_charge` | *What are the currency exchange fees?* |
| `exchange_rate` | *How are the exchange rates determined?* |
| `exchange_via_app` | *Can I exchange USD and GBP from the app?* |
| `fiat_currency_support` | *How many currencies can I have?* |

</details>

<details>
<summary>🧾 <b>Refunds & Disputes</b> — <i>3 classes</i></summary>

| Label | Example Utterance |
|:------|:------------------|
| `direct_debit_payment_not_recognised` | *I have an unauthorized charge.* |
| `Refund_not_showing_up` | *Why can't I see my refund in my statement?* |
| `request_refund` | *I need a refund for something I bought.* |

</details>

<img src="https://user-images.githubusercontent.com/74038190/212284100-561aa473-3905-4a80-b561-0d28506553ee.gif" width="100%">

---

## 🎓 Training Details

<div align="center">

### ⚙️ Hyperparameters

| Parameter | Value | | Parameter | Value |
|:----------|:-----:|-|:----------|:-----:|
| `batch_size` | `(32, 32)` | | `num_epochs` | `(1, 1)` |
| `max_steps` | `-1` | | `sampling_strategy` | `oversampling` |
| `num_iterations` | `2` | | `body_learning_rate` | `2e-05` |
| `head_learning_rate` | `2e-05` | | `loss` | `CosineSimilarityLoss` |
| `distance_metric` | `cosine_distance` | | `margin` | `0.25` |
| `end_to_end` | `False` | | `use_amp` | `False` |
| `warmup_proportion` | `0.1` | | `l2_weight` | `0.01` |
| `seed` | `42` | | `load_best_model_at_end` | `False` |

</div>

### 📚 Training Set Statistics

<div align="center">

| Metric | Min | Median | Max |
|:-------|:---:|:------:|:---:|
| 📝 Word count | **4** | **11.66** | **78** |
| 🏷️ Samples per class | **4** | **4** | **4** |
| 🗂️ Total samples | — | **308** | — |

</div>

### 📉 Training Curve

| Epoch | Step | Training Loss | Validation Loss |
|:-----:|:----:|:-------------:|:---------------:|
| `0.0256` | `1` | **0.2141** | — |

### 🧪 Framework Versions

<div align="center">

![Python](https://img.shields.io/badge/Python-3.13.15-3776AB?style=for-the-badge&logo=python&logoColor=white)
![SetFit](https://img.shields.io/badge/SetFit-1.2.0-FF6F91?style=for-the-badge)
![SentenceTransformers](https://img.shields.io/badge/SentenceTransformers-5.7.0-8A2BE2?style=for-the-badge)
![Transformers](https://img.shields.io/badge/Transformers-5.16.1-FFD21E?style=for-the-badge&logo=huggingface&logoColor=black)
![PyTorch](https://img.shields.io/badge/PyTorch-2.11.0%2Bcu128-EE4C2C?style=for-the-badge&logo=pytorch&logoColor=white)
![Datasets](https://img.shields.io/badge/Datasets-5.0.1-34D399?style=for-the-badge)
![Tokenizers](https://img.shields.io/badge/Tokenizers-0.23.1-F7B32B?style=for-the-badge)

</div>

---

## ⚠️ Bias, Risks & Limitations

<details>
<summary><b>🔍 Click to expand</b></summary>

| ⚠️ Area | 📝 Notes |
|:--------|:---------|
| **Data size** | Only **4 examples per class** — rare phrasings may be misclassified. |
| **Language** | Trained **only on English** — will not generalize to other languages without re-training. |
| **Domain shift** | Vocabulary is banking-specific; out-of-domain inputs may produce confident but wrong labels. |
| **Class ambiguity** | Some classes are semantically close (e.g. `pending_transfer` vs. `transfer_not_received_by_recipient`). |
| **No calibration** | LogReg probabilities are not temperature-calibrated — treat confidence as approximate. |
| **PII** | Do **not** feed real customer PII into shared demos; use anonymized text. |

</details>

### 🚫 Out-of-Scope Use

- ❌ Legal, medical, or financial advice generation
- ❌ Production decision-making without human-in-the-loop
- ❌ Non-English customer messages
- ❌ Emotion / sentiment / toxicity detection

---

## 🧩 Model Card Recipe

```yaml
🎯 base_model:    BAAI/bge-small-en-v1.5
🧠 head:          LogisticRegression
📚 technique:     SetFit (few-shot contrastive)
🏷️ classes:       77
📈 metric:        accuracy
🔤 max_tokens:    512
🌱 seed:          42
```

---

## 🗺️ Roadmap

- [x] Train on 77 banking intents
- [x] Publish to Hugging Face Hub
- [ ] Add calibrated confidence scores
- [ ] Multilingual variant (XLM-R backbone)
- [ ] ONNX / quantized export for edge
- [ ] Evaluation on public banking benchmark

---

## 📜 Citation

If you use this model, please cite the SetFit paper:

```bibtex
@article{tunstall2022setfit,
    doi       = {10.48550/ARXIV.2209.11055},
    url       = {https://arxiv.org/abs/2209.11055},
    author    = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
    keywords  = {Computation and Language (cs.CL), FOS: Computer and information sciences},
    title     = {Efficient Few-Shot Learning Without Prompts},
    publisher = {arXiv},
    year      = {2022},
    copyright = {Creative Commons Attribution 4.0 International}
}
```

---

## 📚 Glossary

| Term | Meaning |
|:-----|:--------|
| **SetFit** | Sentence Transformer Fine-tuning — few-shot text classification technique. |
| **Contrastive Learning** | Training method that pulls similar pairs together, pushes dissimilar apart. |
| **Sentence Transformer** | Encoder that maps text → dense vector embedding. |
| **LogisticRegression Head** | Simple linear classifier on top of embeddings. |
| **Intent** | The user's goal behind a message (e.g. `cancel_transfer`). |

---

## 🌟 Star History

<div align="center">

<a href="https://star-history.com/#TinyModels/setfit-banking-intent&Date">
  <img src="https://api.star-history.com/svg?repos=TinyModels/setfit-banking-intent&type=Date" width="600" alt="Star History Chart"/>
</a>

</div>

---


<div align="center">

### 💜 Made with love by [TinyModels](https://huggingface.co/TinyModels)

<a href="https://huggingface.co/TinyModels/setfit-banking-intent">
  <img src="https://img.shields.io/badge/🤗%20Hugging%20Face-Model%20Card-FFD21E?style=for-the-badge&logoColor=black"/>
</a>
<a href="https://github.com/huggingface/setfit">
  <img src="https://img.shields.io/badge/GitHub-SetFit-181717?style=for-the-badge&logo=github"/>
</a>
<a href="https://arxiv.org/abs/2209.11055">
  <img src="https://img.shields.io/badge/arXiv-2209.11055-B31B1B?style=for-the-badge&logo=arxiv"/>
</a>

<br/><br/>

<img src="https://capsule-render.vercel.app/api?type=waving&color=gradient&customColorList=6,11,20,24,30&height=140&section=footer&text=Thanks%20for%20stopping%20by!&fontSize=24&fontColor=ffffff&animation=twinkling&fontAlignY=60" width="100%"/>

<sub>⭐ If this model helped you, consider leaving a like on the Hub/Repo!</sub>

</div>