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README.md
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* This keyphrase extraction model is very domain-specific and will perform very well on news articles from NY Times. It's not recommended to use this model for other domains, but you are free to test it out.
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* Limited amount of predicted keyphrases.
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* Only works for English documents.
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* For a custom model, please consult the [training notebook]() for more information.
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### ❓ How To Use
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```python
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You can find more information in the [paper](https://arxiv.org/abs/1911.12559).
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## 👷♂️ Training procedure
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For more in detail information, you can take a look at the [training notebook]().
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### Training parameters
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| Parameter | Value |
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|:-----------------:|:----:|:----:|:----:|:----:|:----:|:-----:|:----:|:----:|:----:|
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| KPTimes Test Set | 0.19 | 0.35 | 0.23 | 0.10 | 0.36 | 0.15 | 0.36 | 0.36 | 0.33 |
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For more information on the evaluation process, you can take a look at the keyphrase extraction [evaluation notebook]().
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## 🚨 Issues
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Please feel free to start discussions in the Community Tab.
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* This keyphrase extraction model is very domain-specific and will perform very well on news articles from NY Times. It's not recommended to use this model for other domains, but you are free to test it out.
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* Limited amount of predicted keyphrases.
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* Only works for English documents.
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### ❓ How To Use
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```python
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You can find more information in the [paper](https://arxiv.org/abs/1911.12559).
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## 👷♂️ Training procedure
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### Training parameters
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| Parameter | Value |
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|:-----------------:|:----:|:----:|:----:|:----:|:----:|:-----:|:----:|:----:|:----:|
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| KPTimes Test Set | 0.19 | 0.35 | 0.23 | 0.10 | 0.36 | 0.15 | 0.36 | 0.36 | 0.33 |
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## 🚨 Issues
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Please feel free to start discussions in the Community Tab.
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