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  ---
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- license: mit
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  datasets:
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  - vector-institute/NMB-Plus-Named-Entities
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  base_model:
@@ -8,24 +8,24 @@ pipeline_tag: token-classification
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  tags:
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  - ner
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  - bias_detection
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-
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  model-index:
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  - name: nmb-plus-bias-ner-bert
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  results:
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  - task:
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- type: named-entity-recognition # Required. Example: automatic-speech-recognition
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- name: Named Entity Recognition (NER) # Optional. Example: Speech Recognition
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  dataset:
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- type: vector-institute/NMB-Plus-Named-Entities # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
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- name: Biased Named Entities # Required. A pretty name for the dataset. Example: Common Voice (French)
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  metrics:
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- - type: precision # Required. Example: wer. Use metric id from https://hf.co/metrics
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- value: 0.6405 # Required. Example: 20.90
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- - type: recall
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- value: 0.5589
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- - type: f1
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- value: 0.5922
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-
 
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  ---
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  # Model Overview
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  Total energy consumption for fine-tuning is 0.032804 kWh
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- **Local CO2 Emission:** Approximately 3.12 grams of CO₂ equivalent.
 
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  ---
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+ license: cc
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  datasets:
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  - vector-institute/NMB-Plus-Named-Entities
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  base_model:
 
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  tags:
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  - ner
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  - bias_detection
 
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  model-index:
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  - name: nmb-plus-bias-ner-bert
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  results:
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  - task:
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+ type: named-entity-recognition
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+ name: Named Entity Recognition (NER)
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  dataset:
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+ type: vector-institute/NMB-Plus-Named-Entities
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+ name: Biased Named Entities
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  metrics:
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+ - type: precision
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+ value: 0.6405
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+ - type: recall
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+ value: 0.5589
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+ - type: f1
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+ value: 0.5922
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+ language:
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+ - en
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  ---
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  # Model Overview
 
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  Total energy consumption for fine-tuning is 0.032804 kWh
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+ **Local CO2 Emission:** Approximately 3.12 grams of CO₂ equivalent.