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Librarian Bot: Add base_model information to model (#7)

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- Librarian Bot: Add base_model information to model (c002ece81aefd3c27d62f64f9c05429b368b9786)


Co-authored-by: Librarian Bot (Bot) <librarian-bot@users.noreply.huggingface.co>

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  1. README.md +33 -32
README.md CHANGED
@@ -6,20 +6,28 @@ datasets:
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  - banking77
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  metrics:
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  - accuracy
 
 
 
 
 
 
 
 
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  model-index:
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  - name: distilbert-base-uncased-banking77-classification
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  results:
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  - task:
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- name: Text Classification
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  type: text-classification
 
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  dataset:
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  name: banking77
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  type: banking77
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  args: default
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  metrics:
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- - name: Accuracy
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- type: accuracy
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  value: 0.924025974025974
 
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  - task:
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  type: text-classification
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  name: Text Classification
@@ -29,57 +37,50 @@ model-index:
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  config: default
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  split: test
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  metrics:
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- - name: Accuracy
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- type: accuracy
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  value: 0.924025974025974
 
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  verified: true
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- - name: Precision Macro
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- type: precision
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  value: 0.9278003086307286
 
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  verified: true
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- - name: Precision Micro
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- type: precision
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  value: 0.924025974025974
 
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  verified: true
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- - name: Precision Weighted
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- type: precision
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  value: 0.9278003086307287
 
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  verified: true
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- - name: Recall Macro
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- type: recall
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  value: 0.9240259740259743
 
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  verified: true
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- - name: Recall Micro
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- type: recall
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  value: 0.924025974025974
 
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  verified: true
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- - name: Recall Weighted
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- type: recall
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  value: 0.924025974025974
 
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  verified: true
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- - name: F1 Macro
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- type: f1
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  value: 0.9243068139192414
 
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  verified: true
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- - name: F1 Micro
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- type: f1
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  value: 0.924025974025974
 
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  verified: true
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- - name: F1 Weighted
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- type: f1
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  value: 0.9243068139192416
 
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  verified: true
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- - name: loss
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- type: loss
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  value: 0.31516405940055847
 
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  verified: true
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- widget:
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- - text: 'Can I track the card you sent to me? '
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- example_title: Card Arrival Example
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- - text: Can you explain your exchange rate policy to me?
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- example_title: Exchange Rate Example
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- - text: I can't pay by my credit card
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- example_title: Card Not Working Example
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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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  - banking77
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  metrics:
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  - accuracy
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+ widget:
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+ - text: 'Can I track the card you sent to me? '
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+ example_title: Card Arrival Example
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+ - text: Can you explain your exchange rate policy to me?
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+ example_title: Exchange Rate Example
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+ - text: I can't pay by my credit card
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+ example_title: Card Not Working Example
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+ base_model: distilbert-base-uncased
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  model-index:
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  - name: distilbert-base-uncased-banking77-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: banking77
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  type: banking77
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  args: default
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  metrics:
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+ - type: accuracy
 
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  value: 0.924025974025974
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+ name: Accuracy
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  - task:
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  type: text-classification
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  name: Text Classification
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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: 0.924025974025974
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+ name: Accuracy
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  verified: true
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+ - type: precision
 
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  value: 0.9278003086307286
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+ name: Precision Macro
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  verified: true
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+ - type: precision
 
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  value: 0.924025974025974
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+ name: Precision Micro
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  verified: true
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+ - type: precision
 
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  value: 0.9278003086307287
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+ name: Precision Weighted
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  verified: true
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+ - type: recall
 
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  value: 0.9240259740259743
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+ name: Recall Macro
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  verified: true
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+ - type: recall
 
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  value: 0.924025974025974
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+ name: Recall Micro
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  verified: true
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+ - type: recall
 
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  value: 0.924025974025974
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+ name: Recall Weighted
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  verified: true
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+ - type: f1
 
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  value: 0.9243068139192414
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+ name: F1 Macro
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  verified: true
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+ - type: f1
 
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  value: 0.924025974025974
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+ name: F1 Micro
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  verified: true
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+ - type: f1
 
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  value: 0.9243068139192416
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+ name: F1 Weighted
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  verified: true
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+ - type: loss
 
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  value: 0.31516405940055847
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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