avichr commited on
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Update app.py

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  1. app.py +1 -1
app.py CHANGED
@@ -12,7 +12,7 @@ HebEMO_model = HebEMO()
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  st.title("Emotion Recognition in Hebrew Texts")
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  st.write("HebEMO is a tool to detect polarity and extract emotions from Hebrew user-generated content (UGC), which was trained on a unique Covid-19 related dataset that we collected and annotated. HebEMO yielded a high performance of weighted average F1-score = 0.96 for polarity classification. Emotion detection reached an F1-score of 0.78-0.97, with the exception of *surprise*, which the model failed to capture (F1 = 0.41). More information can be found in our git: https://github.com/avichaychriqui/HeBERT")
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- st.write("Write Hebrew sentences in the text box below to analyze. It takes a while, be patient :). An additional demo can be found in the Colab notebook: https://colab.research.google.com/drive/1Jw3gOWjwVMcZslu-ttXoNeD17lms1-ff ")
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  sent = st.text_area("Text", "ื”ื—ื™ื™ื ื™ืคื™ื ื•ืžืื•ืฉืจื™ื", height = 20)
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  # interact(HebEMO_model.hebemo, text='ื”ื—ื™ื™ื ื™ืคื™ื ื•ืžืื•ืฉืจื™', plot=fixed(True), input_path=fixed(False), save_results=fixed(False),)
 
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  st.title("Emotion Recognition in Hebrew Texts")
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  st.write("HebEMO is a tool to detect polarity and extract emotions from Hebrew user-generated content (UGC), which was trained on a unique Covid-19 related dataset that we collected and annotated. HebEMO yielded a high performance of weighted average F1-score = 0.96 for polarity classification. Emotion detection reached an F1-score of 0.78-0.97, with the exception of *surprise*, which the model failed to capture (F1 = 0.41). More information can be found in our git: https://github.com/avichaychriqui/HeBERT")
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+ st.write("Write Hebrew sentences in the text box below to analyze (each sentence in a different rew). It takes a while, be patient :). An additional demo can be found in the Colab notebook: https://colab.research.google.com/drive/1Jw3gOWjwVMcZslu-ttXoNeD17lms1-ff ")
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  sent = st.text_area("Text", "ื”ื—ื™ื™ื ื™ืคื™ื ื•ืžืื•ืฉืจื™ื", height = 20)
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  # interact(HebEMO_model.hebemo, text='ื”ื—ื™ื™ื ื™ืคื™ื ื•ืžืื•ืฉืจื™', plot=fixed(True), input_path=fixed(False), save_results=fixed(False),)