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Mykes
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rubert_ner_SDDCS

Token Classification
Transformers
Safetensors
Russian
bert
biology
medical
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@@ -43,18 +43,18 @@ The fine-tuned model has achieved the following performance metrics:
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  ```
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  precision recall f1-score support
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- AGE 1.00 1.00 1.00 320
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- CITY 0.99 1.00 1.00 2677
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- DISEASE 0.98 1.00 0.99 3192
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- DRUG 0.99 1.00 0.99 3949
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- GENDER 0.99 1.00 1.00 364
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- SPECIALITY 0.94 0.98 0.96 2114
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- SUBWAY 0.99 1.00 0.99 503
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- SYMPTOM 0.98 0.99 0.99 4461
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- micro avg 0.98 0.99 0.99 17580
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- macro avg 0.98 1.00 0.99 17580
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- weighted avg 0.98 0.99 0.99 17580
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  ```
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  ## When to use
 
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  ```
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  precision recall f1-score support
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+ AGE 1.00 1.00 1.00 583
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+ CITY 1.00 1.00 1.00 5244
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+ DISEASE 0.99 1.00 1.00 6569
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+ DRUG 1.00 1.00 1.00 8220
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+ GENDER 1.00 1.00 1.00 664
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+ SPECIALITY 1.00 0.98 0.99 4207
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+ SUBWAY 1.00 1.00 1.00 1084
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+ SYMPTOM 1.00 1.00 1.00 8979
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+ micro avg 1.00 1.00 1.00 35550
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+ macro avg 1.00 1.00 1.00 35550
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+ weighted avg 1.00 1.00 1.00 35550
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  ```
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  ## When to use