Librarian Bot: Add base_model information to model

#2
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  1. README.md +22 -21
README.md CHANGED
@@ -1,13 +1,12 @@
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  ---
 
 
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  license: apache-2.0
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  tags:
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  - generated_from_trainer
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  - named-entity-recognition
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  - russian
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  - ner
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- language:
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- - ru
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- thumbnail: "Sberbank RuBERT-base fintuned on Collection3 dataset"
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  datasets:
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  - RCC-MSU/collection3
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  metrics:
@@ -15,12 +14,14 @@ metrics:
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  - recall
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  - f1
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  - accuracy
 
 
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  model-index:
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  - name: sberbank-rubert-base-collection3
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  results:
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  - task:
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- name: Token Classification
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  type: token-classification
 
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  dataset:
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  name: RCC-MSU/collection3
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  type: named-entity-recognition
@@ -28,21 +29,21 @@ model-index:
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  split: validation
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  args: default
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  metrics:
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- - name: Precision
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- type: precision
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  value: 0.938019472809309
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- - name: Recall
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- type: recall
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  value: 0.9594364828758805
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- - name: F1
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- type: f1
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  value: 0.9486071085494716
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- - name: Accuracy
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- type: accuracy
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  value: 0.9860420020488805
 
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  - task:
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- name: Token Classification
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  type: token-classification
 
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  dataset:
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  name: RCC-MSU/collection3
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  type: named-entity-recognition
@@ -50,18 +51,18 @@ model-index:
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  split: test
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  args: default
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  metrics:
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- - name: Precision
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- type: precision
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  value: 0.9419896321895829
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- - name: Recall
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- type: recall
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  value: 0.9537615596100975
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- - name: F1
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- type: f1
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  value: 0.947839046199702
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- - name: Accuracy
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- type: accuracy
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  value: 0.9847255179564897
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  ---
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+ language:
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+ - ru
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  license: apache-2.0
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  tags:
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  - generated_from_trainer
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  - named-entity-recognition
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  - russian
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  - ner
 
 
 
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  datasets:
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  - RCC-MSU/collection3
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  metrics:
 
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  - recall
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  - f1
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  - accuracy
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+ thumbnail: Sberbank RuBERT-base fintuned on Collection3 dataset
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+ base_model: sberbank-ai/ruBert-base
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  model-index:
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  - name: sberbank-rubert-base-collection3
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  results:
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  - task:
 
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  type: token-classification
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+ name: Token Classification
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  dataset:
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  name: RCC-MSU/collection3
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  type: named-entity-recognition
 
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  split: validation
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  args: default
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  metrics:
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+ - type: precision
 
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  value: 0.938019472809309
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+ name: Precision
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+ - type: recall
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  value: 0.9594364828758805
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+ name: Recall
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+ - type: f1
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  value: 0.9486071085494716
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+ name: F1
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+ - type: accuracy
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  value: 0.9860420020488805
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+ name: Accuracy
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  - task:
 
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  type: token-classification
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+ name: Token Classification
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  dataset:
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  name: RCC-MSU/collection3
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  type: named-entity-recognition
 
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  split: test
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  args: default
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  metrics:
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+ - type: precision
 
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  value: 0.9419896321895829
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+ name: Precision
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+ - type: recall
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  value: 0.9537615596100975
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+ name: Recall
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+ - type: f1
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  value: 0.947839046199702
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+ name: F1
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+ - type: accuracy
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  value: 0.9847255179564897
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+ name: Accuracy
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You