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README.md
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pipeline_tag: text-classification
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---
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```python
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import torch.nn as nn
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from huggingface_hub import PyTorchModelHubMixin
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pipeline_tag: text-classification
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---
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**Title:** IndoBERT-EcommerceReview (v1.0)
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**Short Summary:**
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A fine-tuned IndoBERT model for multi-label classification of customer reviews in e-commerce, focusing on product quality, customer service, and shipping/delivery.
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**Detailed Description:**
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Explain that the model is based on IndoBERT-base-p1, a pre-trained IndoBERT model specifically designed for Indonesian text.
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Highlight that it's fine-tuned on a dataset of e-commerce reviews, allowing it to understand the nuances of customer sentiment in this domain.
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Clearly define the three output classes and their corresponding labels:
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- Produk (Product): Customer satisfaction with product quality, performance, and description accuracy.
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- Layanan Pelanggan (Customer Service): Interaction with sellers, their responsiveness, and complaint handling.
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- Pengiriman (Shipping/Delivery): Speed of delivery, item condition upon arrival, and timeliness.
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Optionally, provide brief examples of reviews that would fall into each category to further illustrate how the model interprets sentiment.
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**How to import in PyTorch:**
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```python
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import torch.nn as nn
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from huggingface_hub import PyTorchModelHubMixin
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