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Update README.md

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@@ -9,6 +9,31 @@ widget:
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  - text: "Nazywam się Grzegorz Brzęszczyszczykiewicz, pochodzę z Chrząszczyżewoszczyc, pracuję w Łękołodzkim Urzędzie Powiatowym"
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  - text: "Jestem Krzysiek i pracuję w Ministerstwie Sportu"
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  - text: "Na imię jej Wiktoria, pracuje w Krakowie na AGH"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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@@ -21,14 +46,6 @@ It has been trained to recognize three types of entities: person (PER), location
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  Specifically, this model is an [*allegro/herbert-base-cased*](https://huggingface.co/allegro/herbert-base-cased) model that was fine-tuned on the Polish subset of *wikiann* dataset.
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- It achieves the following results on the test subset of *wikitest/pl* set:
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- - Loss: 0.1937
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- - Precision: 0.8857
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- - Recall: 0.9070
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- - F1: 0.8962
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- - Accuracy: 0.9581
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-
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-
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  ## Intended uses & limitations
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  #### How to use
 
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  - text: "Nazywam się Grzegorz Brzęszczyszczykiewicz, pochodzę z Chrząszczyżewoszczyc, pracuję w Łękołodzkim Urzędzie Powiatowym"
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  - text: "Jestem Krzysiek i pracuję w Ministerstwie Sportu"
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  - text: "Na imię jej Wiktoria, pracuje w Krakowie na AGH"
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+ model-index:
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+ - name: herbert-base-ner
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+ results:
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+ - task:
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+ name: Named Entity Recognition
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+ type: token-classification
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+ dataset:
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+ name: wikiann
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+ type: wikiann
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+ config: pl
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+ split: test
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+ args: pl
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+ metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.8857142857142857
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+ - name: Recall
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+ type: recall
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+ value: 0.9070532179048386
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+ - name: F1
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+ type: f1
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+ value: 0.896256755412619
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9581463871961428
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  ---
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  Specifically, this model is an [*allegro/herbert-base-cased*](https://huggingface.co/allegro/herbert-base-cased) model that was fine-tuned on the Polish subset of *wikiann* dataset.
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  ## Intended uses & limitations
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  #### How to use