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README.md

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 # RobBERTje finetuned for sentiment analysis on DBRD
 
-This is a finetuned model based on [RobBERTje (non-shuffled)](https://huggingface.co/DTAI-KULeuven/robbertje-1-gb-non-shuffled). We used [DBRD](https://huggingface.co/datasets/dbrd), which consists of book reviews from [hebban.nl](hebban.nl). Hence our example sentences about books. We did some limited experiments to test if this also works for other domains, but this was not 
+This is a finetuned model based on [RobBERTje (merged)](https://huggingface.co/DTAI-KULeuven/robbertje-1-gb-non-shuffled). We used [DBRD](https://huggingface.co/datasets/dbrd), which consists of book reviews from [hebban.nl](hebban.nl). Hence our example sentences about books. We did some limited experiments to test if this also works for other domains, but this was not exactly amazing. 
+
+We released a distilled model and a `base`-sized model. Both models perform quite well, so there is only a slight performance tradeoff:
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+| Model                                                                                   | #Params.  | Accuracy  |
+|-----------------------------------------------------------------------------------------|-----------|-----------|
+| [RobBERT (v2)](https://huggingface.co/DTAI-KULeuven/robbert-v2-dutch-sentiment)         | 110 M     |94.4       | 
+| [Merged (p=0.5)](https://huggingface.co/DTAI-KULeuven/robbertje-merged-dutch-sentiment) | 74 M      |92.9       |
 
 # Training data and setup
 We used the [Dutch Book Reviews Dataset (DBRD)](https://huggingface.co/datasets/dbrd) from van der Burgh et al. (2019).