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@@ -6,6 +6,62 @@ datasets:
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  - emotion
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  metrics:
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  - 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
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  - emotion
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  metrics:
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  - accuracy
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+ model-index:
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+ - name: autoevaluate/multi-class-classification
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+ results:
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+ - task:
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+ type: text-classification
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+ name: Text Classification
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+ dataset:
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+ name: emotion
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+ type: emotion
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+ config: default
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+ split: test
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+ metrics:
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+ - type: accuracy
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+ value: 0.9185
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+ name: Accuracy
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+ verified: true
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+ - type: precision
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+ value: 0.8738350796775306
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+ name: Precision Macro
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+ verified: true
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+ - type: precision
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+ value: 0.9185
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+ name: Precision Micro
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+ verified: true
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+ - type: precision
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+ value: 0.9179425177997311
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+ name: Precision Weighted
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+ verified: true
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+ - type: recall
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+ value: 0.8650962919021573
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+ name: Recall Macro
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+ verified: true
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+ - type: recall
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+ value: 0.9185
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+ name: Recall Micro
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+ verified: true
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+ - type: recall
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+ value: 0.9185
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+ name: Recall Weighted
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+ verified: true
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+ - type: f1
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+ value: 0.8692821860210945
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+ name: F1 Macro
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+ verified: true
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+ - type: f1
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+ value: 0.9185
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+ name: F1 Micro
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+ verified: true
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+ - type: f1
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+ value: 0.9181177508591364
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+ name: F1 Weighted
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+ verified: true
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+ - type: loss
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+ value: 0.20907790958881378
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+ name: loss
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+ verified: true
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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