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README.md
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metrics:
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- accuracy
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library_name: transformers
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---
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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# dipawidia/xlnet-base-cased-product-review-sentiment-analysis
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This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on any type of product reviews dataset gathered from several e-commerce such as shopee, tokopedia, blibli, lazada, and zalora.
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It achieves the following results on the evaluation set:
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- Train Loss: 0.1085
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- Train Accuracy: 0.9617
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Negative
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```
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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metrics:
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- accuracy
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library_name: transformers
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datasets:
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- dipawidia/ecommerce-product-reviews-sentiment
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---
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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# dipawidia/xlnet-base-cased-product-review-sentiment-analysis
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This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on any type of product reviews dataset gathered from several e-commerce such as shopee, tokopedia, blibli, lazada, and zalora.
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The dataset can be found [here](https://huggingface.co/dipawidia/ecommerce-product-reviews-sentiment)
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It achieves the following results on the evaluation set:
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- Train Loss: 0.1085
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- Train Accuracy: 0.9617
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Negative
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```
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## Training procedure
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### Training hyperparameters
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