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@@ -26,9 +26,14 @@ auc: 0.957133746355685
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  accuracy: 0.8831168831168831
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  ## Trained on
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  Twitter_Non-Ads from the paper "Stress Detection from Social Media Articles: New Dataset Benchmark and Analytical Study" - 2022 International Joint Conference on Neural Networks (IJCNN)
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  All credit relating to the dataset goes to authors Aryan Rastogi; Qian Liu; Erik Cambria
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  accuracy: 0.8831168831168831
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+ ## Fine-tuned from
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+ cardiffnlp/twitter-roberta-base-sentiment-latest
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  ## Trained on
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  Twitter_Non-Ads from the paper "Stress Detection from Social Media Articles: New Dataset Benchmark and Analytical Study" - 2022 International Joint Conference on Neural Networks (IJCNN)
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  All credit relating to the dataset goes to authors Aryan Rastogi; Qian Liu; Erik Cambria
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+ Access to dataset: https://github.com/aryan-r22/Stress-Detection_Social-Media-Articles/tree/main