Update README.md
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@ -65,4 +65,20 @@ outputs = predict(path, sampling_rate)
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{'Emotion': 'fear', 'Score': '0.4%'},
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{'Emotion': 'happiness', 'Score': '0.7%'},
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{'Emotion': 'sadness', 'Score': '0.5%'}]
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~~~
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~~~
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## Evaluation
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The following tables summarize the scores obtained by model overall and per each class.
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| Emotions | precision | recall | f1-score | accuracy |
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|-----------|-----------|--------|----------|----------|
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| anger | 0.82 | 1.00 | 0.81 | |
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| disgust | 0.85 | 0.96 | 0.85 | |
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| fear | 0.78 | 0.88 | 0.80 | |
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| happiness | 0.84 | 0.71 | 0.78 | |
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| sadness | 0.86 | 1.00 | 0.79 | |
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| | | | Overall | 0.806 |
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##
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