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by z-dickson - opened
README.md
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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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It achieves the following results on the evaluation set:
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- Validation Sparse Categorical Accuracy: 0.6434
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- Epoch: 4
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## Model description
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More information needed
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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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More information needed
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## Training procedure
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### Training hyperparameters
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- Transformers 4.26.0
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- TensorFlow 2.9.2
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- Tokenizers 0.13.2
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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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Polish: Fakt, Rzeczpospolita, Gazeta Wyborcza
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English: The Times, The Guardian, The Sun
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Dutch: De Telegraaf, NRC, Volkskrant
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Spanish: El Mundo, El Pais, ABC
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German: Suddeutsche Zeitung, De Welt, Bild
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coding scheme:
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- "LABEL_0": negative,
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- "LABEL_1": neutral,
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- "LABEL_2": "positive"
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It achieves the following results on the evaluation set:
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- Validation Sparse Categorical Accuracy: 0.6434
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- Epoch: 4
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### Training hyperparameters
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- Transformers 4.26.0
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- TensorFlow 2.9.2
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- Tokenizers 0.13.2
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