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--- |
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tags: |
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- pytorch_model_hub_mixin |
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- model_hub_mixin |
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- indobert |
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- indobenchmark |
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- indonlu |
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datasets: |
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- fahrendrakhoirul/ecommerce-reviews-multilabel-dataset |
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language: |
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- id |
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metrics: |
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- f1 |
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- recall |
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- precision |
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library_name: transformers |
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pipeline_tag: text-classification |
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--- |
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**Title:** IndoBERT-EcommerceReview |
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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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from transformers import BertModel, AutoTokenizer |
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class IndoBertEcommerceReview(nn.Module, PyTorchModelHubMixin): |
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def __init__(self, bert): |
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super().__init__() |
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self.bert = bert |
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self.sigmoid = nn.Sigmoid() |
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def forward(self, input_ids, attention_mask): |
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outputs = self.bert(input_ids=input_ids, attention_mask=attention_mask) |
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logits = outputs.logits |
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probabilities = self.sigmoid(logits) |
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return probabilities |
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bert = BertModel.from_pretrained("indobenchmark/indobert-base-p1") |
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tokenizer = AutoTokenizer.from_pretrained("fahrendrakhoirul/indobert-finetuned-ecommerce-reviews") |
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model = IndoBertEcommerceReview.from_pretrained("fahrendrakhoirul/indobert-finetuned-ecommerce-reviews", bert=bert) |
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``` |
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This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: |
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- Library: [More Information Needed] |
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- Docs: [More Information Needed] |
