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Update README.md

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@@ -61,4 +61,40 @@ print(sentence.to_tagged_string())
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  This yields the following output:
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  ```
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  مقامات <NOUN> مصری <ADJ> به <ADP> خاطر <NOUN> حفظ <NOUN> ثبات <NOUN> کشور <NOUN> در <ADP> منطقهای <NOUN> پرآشوب <ADJ> بر <ADP> خود <PRON> میبالند <VERB> . <PUNCT>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
 
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  This yields the following output:
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  ```
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  مقامات <NOUN> مصری <ADJ> به <ADP> خاطر <NOUN> حفظ <NOUN> ثبات <NOUN> کشور <NOUN> در <ADP> منطقهای <NOUN> پرآشوب <ADJ> بر <ADP> خود <PRON> میبالند <VERB> . <PUNCT>
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+ ```
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+
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+ ---
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+
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+ ### Results
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+ - F-score (micro) 0.9773
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+ - F-score (macro) 0.9461
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+ - Accuracy 0.9773
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+
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+ ```
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+ By class:
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+ precision recall f1-score support
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+
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+ NOUN 0.9770 0.9849 0.9809 6420
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+ ADP 0.9947 0.9916 0.9932 1909
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+ ADJ 0.9342 0.9128 0.9234 1525
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+ PUNCT 1.0000 1.0000 1.0000 1365
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+ VERB 0.9840 0.9711 0.9775 1141
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+ CCONJ 0.9912 0.9937 0.9925 794
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+ AUX 0.9622 0.9799 0.9710 546
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+ PRON 0.9751 0.9865 0.9808 517
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+ SCONJ 0.9797 0.9757 0.9777 494
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+ NUM 0.9948 1.0000 0.9974 385
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+ ADV 0.9343 0.9033 0.9185 362
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+ DET 0.9773 0.9711 0.9742 311
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+ PART 0.9916 1.0000 0.9958 237
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+ INTJ 0.8889 0.8000 0.8421 10
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+ X 0.7143 0.6250 0.6667 8
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+
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+ micro avg 0.9773 0.9773 0.9773 16024
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+ macro avg 0.9533 0.9397 0.9461 16024
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+ weighted avg 0.9772 0.9773 0.9772 16024
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+ samples avg 0.9773 0.9773 0.9773 16024
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+
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+ Loss: 0.12471389770507812
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+
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  ```