ml6team
/
keyphrase-extraction-distilbert-inspec
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Update README.md

This commit is contained in:
Thomas De Decker 2022-08-19 11:52:01 +00:00 committed by huggingface-web
parent d7a71e2208
commit a2a1881947
1 changed files with 0 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

5
README.md
View File

@ -65,7 +65,6 @@ Sahrawat, Dhruva, Debanjan Mahata, Haimin Zhang, Mayank Kulkarni, Agniv Sharma,
### 🛑 Limitations ### 🛑 Limitations
* This keyphrase extraction model is very domain-specific and will perform very well on abstracts of scientific papers. It's not recommended to use this model for other domains, but you are free to test it out. * This keyphrase extraction model is very domain-specific and will perform very well on abstracts of scientific papers. It's not recommended to use this model for other domains, but you are free to test it out.
* Only works for English documents. * Only works for English documents.
* For a custom model, please consult the [training notebook]() for more information.
### ❓ How To Use ### ❓ How To Use
```python ```python
@ -139,8 +138,6 @@ print(keyphrases)
You can find more information in the [paper](https://dl.acm.org/doi/10.3115/1119355.1119383). You can find more information in the [paper](https://dl.acm.org/doi/10.3115/1119355.1119383).
## 👷‍♂️ Training Procedure ## 👷‍♂️ Training Procedure
For more in detail information, you can take a look at the [training notebook]().
### Training Parameters ### Training Parameters
| Parameter | Value | | Parameter | Value |
@ -256,7 +253,5 @@ The model achieves the following results on the Inspec test set:
|:-----------------:|:----:|:----:|:----:|:----:|:----:|:-----:|:----:|:----:|:----:| |:-----------------:|:----:|:----:|:----:|:----:|:----:|:-----:|:----:|:----:|:----:|
| Inspec Test Set | 0.45 | 0.40 | 0.39 | 0.33 | 0.53 | 0.38 | 0.47 | 0.57 | 0.49 | | Inspec Test Set | 0.45 | 0.40 | 0.39 | 0.33 | 0.53 | 0.38 | 0.47 | 0.57 | 0.49 |
For more information on the evaluation process, you can take a look at the keyphrase extraction [evaluation notebook]().
## 🚨 Issues ## 🚨 Issues
Please feel free to start discussions in the Community Tab. Please feel free to start discussions in the Community Tab.