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mox
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gBERt_base_twitter_sentiment_politicians

German
Text Classification
sentiment
Simpletransformers
deepset/gbert-base
Model card Files Community
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Update README.md

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@@ -33,14 +33,17 @@ In this case for the output:
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  - 2 = neutral
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  Example for a positive prediction:
 
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  model.predict(["Das ist gut! Wir danken dir."])
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  ([0], array([[ 2.06561327, -3.57908797, 1.5340755 ]]))
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  Example for a negative prediction:
 
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  model.predict(["Ich hasse dich!"])
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  ([1], array([[-3.50486898, 4.29590368, -0.9000684 ]]))
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  Example for a neutral prediction:
 
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  model.predict(["Heute ist Sonntag."])
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  ([2], array([[-2.94458342, -2.91875601, 4.94414234]]))
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  - 2 = neutral
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  Example for a positive prediction:
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+
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  model.predict(["Das ist gut! Wir danken dir."])
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  ([0], array([[ 2.06561327, -3.57908797, 1.5340755 ]]))
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  Example for a negative prediction:
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+
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  model.predict(["Ich hasse dich!"])
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  ([1], array([[-3.50486898, 4.29590368, -0.9000684 ]]))
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  Example for a neutral prediction:
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+
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  model.predict(["Heute ist Sonntag."])
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  ([2], array([[-2.94458342, -2.91875601, 4.94414234]]))
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