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πŸ“ Dataset Card: Customer Complaints Classification
🧾 Dataset Description
This dataset contains 3,800 real-world customer complaint entries submitted to a business platform. Each complaint includes a short text description and is labeled with two targets:

Category β€” what type of issue the complaint relates to (e.g., Payments, Promotions, Account & Shipping, Order Tracking).

Urgency β€” how urgent the user perceives the issue (Low, Medium, or Immediate).

The dataset is designed for multi-output text classification tasks and is especially useful for training models that can understand intent and urgency in customer service interactions.

πŸ“‚ Structure
Each entry contains the following fields:

Complaint: A natural language description of the customer issue.

Category: The type of problem (business area).

Urgency: The urgency level for customer support triaging.

Example:

csv
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Complaint,Category,Urgency
"I can’t add a new address β€” button does nothing.",Account & Shipping,Low
"System declined my payment without any reason β€” this is very frustrating.",Payments,Immediate
πŸ” Use Cases
Training customer service models to triage tickets automatically.

Developing multi-task transformers (e.g., T5, BART) that output structured intent + urgency.

Benchmarking multi-label text classification models in a practical domain.

Fine-tuning LLMs for support automation or chatbot prioritization.

🧠 Tasks
Text Classification (Multi-output / Multi-label)

Intent Recognition

Urgency Detection

Natural Language Understanding

πŸš€ Recommended Models
T5 / BART for sequence-to-sequence learning

DistilBERT / RoBERTa for classification pipelines

Any encoder-decoder or encoder-only transformer model


![Screenshot 2025-05-13 025746.png](https://cdn-uploads.huggingface.co/production/uploads/66ebb498561b0d0436e5e35f/_fSwtUVf8H4btpuUsAuh1.png)

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  1. README.md +17 -0
README.md CHANGED
@@ -20,6 +20,23 @@ configs:
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  data_files:
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  - split: train
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  path: data/train-*
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # Dataset Card for "ecommerce-customer-support"
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  data_files:
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  - split: train
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  path: data/train-*
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+ license: mit
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+ task_categories:
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+ - text-classification
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+ - text2text-generation
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+ language:
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+ - en
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+ tags:
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+ - customer-support
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+ - t5
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+ - business
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+ - classification
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+ - urgency-detection
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+ - multi-label
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+ - complaints
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+ pretty_name: 'Customer Complaints Classification '
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+ size_categories:
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+ - 1K<n<10K
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  ---
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  # Dataset Card for "ecommerce-customer-support"
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