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  results: []
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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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- probably proofread and complete it, then remove this comment. -->
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  # multilingual_sentiment_newspaper_headlines
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- This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
 
 
 
 
 
 
 
 
 
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  It achieves the following results on the evaluation set:
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  - Train Loss: 0.2886
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  - Train Sparse Categorical Accuracy: 0.8688
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  ## Intended uses & limitations
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- More information needed
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  ## Training and evaluation data
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  results: []
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  ---
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  # multilingual_sentiment_newspaper_headlines
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+ This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on a dataset of 30k newspaper headlines in German, Polish, English, Dutch and Spanish. The dataset contains 6k headlines in each of the five languages. The newspapers used are as follows:
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+ ['fakt', 'Rzeczpospolita', 'gazeta_wyborcza', 'UK_times',
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+ 'guardian', 'UK_sun', 'NRC', 'de_telegraaf', 'volkskrant',
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+ 'el_mundo', 'el_pais', 'ABC_spain', 'suddeutsche_zeitung',
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+ 'De_Welt', 'Bild']
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  It achieves the following results on the evaluation set:
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  - Train Loss: 0.2886
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  - Train Sparse Categorical Accuracy: 0.8688
 
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  ## Intended uses & limitations
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+ Newpaper headline classification
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  ## Training and evaluation data
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