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Update README.md
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README.md
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A SetFit model fit on 166 downlsampled multilingual IPTC Subject labels (concatenated for the lowest hierarchy level into artificial sentences of keywords) to predict the mid level news categories.
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The purpose of this classifier is to support exploring corpora as weak labeler, since the representations of these descriptions are only approximations of real documents from those topics.
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Accuracy on highest level labels in eval:
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0.9779412
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Accuracy/F1/mcc on mid level labels in eval:
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A SetFit model fit on 166 downlsampled multilingual IPTC Subject labels (concatenated for the lowest hierarchy level into artificial sentences of keywords) to predict the mid level news categories.
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The purpose of this classifier is to support exploring corpora as weak labeler, since the representations of these descriptions are only approximations of real documents from those topics.
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The dataset I used to train the model is based on this file:
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https://huggingface.co/datasets/KnutJaegersberg/News_topics_IPTC_codes_long
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Accuracy on highest level labels in eval:
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0.9779412
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Accuracy/F1/mcc on mid level labels in eval:
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