W-L/Customer-service-tickets-qwen-qa

---
license: cc-by-nc-4.0
pretty_name: Customer Support Tickets QA en SFT
size_categories:
- 10K<n<100K
task_categories:
- text-generation
- question-answering
- text-classification
language:
- en
tags:
- customer-support
- helpdesk
- tickets
- instruction-tuning
- sft
- qwen
configs:
- config_name: default
data_files:
- split: train
path: customer_support_tickets_en_qwen3_5.jsonl
---

# Customer Support Tickets QA (English) — Qwen SFT Dataset

This dataset is formatted for **supervised fine-tuning (SFT)** of Qwen-style chat models on customer support email tasks. source dataset: Tobi-Bueck/customer-support-tickets

It is designed for training models to read a customer ticket, understand its context, and generate an appropriate support response. Depending on the prompt design, the same data can also support auxiliary tasks such as queue prediction, priority prediction, and ticket type classification.

## Dataset Format

The training file is:

- `customer_support_tickets_en_qwen3_5.jsonl`

Each row is a single SFT example in a **Qwen chat template–compatible structure**.

Typical source fields described by the original dataset include:

- **queue**: department responsible for handling the ticket
- **priority**: urgency level of the issue
- **language**: language of the ticket
- **subject**: subject line of the customer email
- **body**: full customer message
- **answer**: support agent response
- **type**: ticket type, such as Incident, Request, Problem, or Change
- **business_type**: domain of the helpdesk or company
- **tags**: issue labels or categories

These fields are reflected in the prompt so the model can learn both response generation and structured reasoning over ticket metadata.

## Intended Use

This dataset is intended for:

- **Instruction tuning / supervised fine-tuning**
- **Customer support response generation**
- **Ticket understanding**
- **Synthetic helpdesk assistant training**