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@@ -220,6 +220,8 @@ The news texts were extracted from the [MaCoCu-Genre web corpora](http://hdl.han
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  The training dataset was automatically annotated with the IPTC Media Topic labels by
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  the [GPT-4o](https://platform.openai.com/docs/models/gpt-4o) model (yielding 0.72 micro-F1 and 0.73 macro-F1 on the test dataset).
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  Label distribution in the training dataset:
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  | labels | count | proportion |
 
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  The training dataset was automatically annotated with the IPTC Media Topic labels by
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  the [GPT-4o](https://platform.openai.com/docs/models/gpt-4o) model (yielding 0.72 micro-F1 and 0.73 macro-F1 on the test dataset).
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+ The code for the development and evaluation of the model is available on [this GitHub repository](https://github.com/TajaKuzman/IPTC-Media-Topic-Classification).
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  Label distribution in the training dataset:
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  | labels | count | proportion |