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README.md
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The performance of the pretrained model was evaluated using [ScandEval](https://github.com/ScandEval/ScandEval).
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| task | dataset | summary
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The performance of the pretrained model was evaluated using [ScandEval](https://github.com/ScandEval/ScandEval).
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| task | dataset | summary |
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|:-------------------------|:-------------|:-------------------------------------------------------------------------------------------|
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| sentiment-classification | swerec | mcc = 63.02, mcc_se = 2.16, macro_f1 = 62.2, macro_f1_se = 3.61 |
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| sentiment-classification | angry-tweets | mcc = 47.21, mcc_se = 0.53, macro_f1 = 64.21, macro_f1_se = 0.53 |
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| sentiment-classification | norec | mcc = 42.23, mcc_se = 8.69, macro_f1 = 57.24, macro_f1_se = 7.67 |
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| named-entity-recognition | suc3 | micro_f1 = 50.03, micro_f1_se = 4.16, micro_f1_no_misc = 53.55, micro_f1_no_misc_se = 4.57 |
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| named-entity-recognition | dane | micro_f1 = 76.44, micro_f1_se = 1.36, micro_f1_no_misc = 80.61, micro_f1_no_misc_se = 1.11 |
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| named-entity-recognition | norne-nb | micro_f1 = 68.38, micro_f1_se = 1.72, micro_f1_no_misc = 73.08, micro_f1_no_misc_se = 1.66 |
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| named-entity-recognition | norne-nn | micro_f1 = 60.45, micro_f1_se = 1.71, micro_f1_no_misc = 64.39, micro_f1_no_misc_se = 1.8 |
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| linguistic-acceptability | scala-sv | mcc = 5.01, mcc_se = 5.41, macro_f1 = 49.46, macro_f1_se = 3.67 |
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| linguistic-acceptability | scala-da | mcc = 54.74, mcc_se = 12.22, macro_f1 = 76.25, macro_f1_se = 6.09 |
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| linguistic-acceptability | scala-nb | mcc = 19.18, mcc_se = 14.01, macro_f1 = 55.3, macro_f1_se = 8.85 |
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| linguistic-acceptability | scala-nn | mcc = 5.72, mcc_se = 5.91, macro_f1 = 49.56, macro_f1_se = 3.73 |
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| question-answering | scandiqa-da | em = 26.36, em_se = 1.17, f1 = 32.41, f1_se = 1.1 |
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| question-answering | scandiqa-no | em = 26.14, em_se = 1.59, f1 = 32.02, f1_se = 1.59 |
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| question-answering | scandiqa-sv | em = 26.38, em_se = 1.1, f1 = 32.33, f1_se = 1.05 |
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| speed | speed | speed = 4.55, speed_se = 0.0 |
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