lewtun HF staff commited on
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Add evaluation results on the autoevaluate--conll2003-sample config and test split of autoevaluate/conll2003-sample

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Beep boop, I am a bot from Hugging Face's automatic model evaluator 👋!\
Your model has been evaluated on the autoevaluate--conll2003-sample config and test split of the [autoevaluate/conll2003-sample](https://huggingface.co/datasets/autoevaluate/conll2003-sample) dataset by

@lewtun

, using the predictions stored [here](https://huggingface.co/datasets/autoevaluate/autoeval-staging-eval-project-e2e28e52-014f-41d6-a473-008f1f5e4d3d-6058).\
Accept this pull request to see the results displayed on the [Hub leaderboard](https://huggingface.co/spaces/autoevaluate/leaderboards?dataset=autoevaluate/conll2003-sample).\
Evaluate your model on more datasets [here](https://huggingface.co/spaces/autoevaluate/model-evaluator?dataset=autoevaluate/conll2003-sample).

Files changed (1) hide show
  1. README.md +66 -25
README.md CHANGED
@@ -14,50 +14,91 @@ model-index:
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  - name: entity-extraction
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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: conll2003
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  type: conll2003
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  args: conll2003
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  metrics:
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- - name: Precision
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- type: precision
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  value: 0.8862817854414493
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- - name: Recall
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- type: recall
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  value: 0.9084908826490659
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- - name: F1
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- type: f1
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  value: 0.8972489227709645
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- - name: Accuracy
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- type: accuracy
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  value: 0.9774889986814304
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - task:
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  type: token-classification
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- name: entity_extraction
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  dataset:
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- type: conll2003
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- name: conll2003
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- config: conll2003
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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: 0.9703231821006837
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  verified: true
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- - name: Precision
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- type: precision
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- value: 0.9758137392136365
 
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  verified: true
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- - name: Recall
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- type: recall
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- value: 0.9764192759122017
 
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  verified: true
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- - name: F1 Score
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- type: f1
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- value: 0.9761164136513085
 
 
 
 
 
 
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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
 
14
  - name: entity-extraction
15
  results:
16
  - task:
 
17
  type: token-classification
18
+ name: Token Classification
19
  dataset:
20
  name: conll2003
21
  type: conll2003
22
  args: conll2003
23
  metrics:
24
+ - type: precision
 
25
  value: 0.8862817854414493
26
+ name: Precision
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+ - type: recall
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  value: 0.9084908826490659
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+ name: Recall
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+ - type: f1
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  value: 0.8972489227709645
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+ name: F1
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+ - type: accuracy
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  value: 0.9774889986814304
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+ name: Accuracy
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+ - type: accuracy
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+ value: 0.9703231821006837
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+ name: Accuracy
39
+ verified: true
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+ - type: precision
41
+ value: 0.9758137392136365
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+ name: Precision
43
+ verified: true
44
+ - type: recall
45
+ value: 0.9764192759122017
46
+ name: Recall
47
+ verified: true
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+ - type: f1
49
+ value: 0.9761164136513085
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+ name: F1 Score
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+ verified: true
52
+ - type: accuracy
53
+ value: 0.9703231821006837
54
+ name: Accuracy
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+ verified: true
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+ - type: precision
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+ value: 0.9758137392136365
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+ name: Precision
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+ verified: true
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+ - type: recall
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+ value: 0.9764192759122017
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+ name: Recall
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+ verified: true
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+ - type: f1
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+ value: 0.9761164136513085
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+ name: F1 Score
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+ verified: true
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  - task:
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  type: token-classification
70
+ name: Token Classification
71
  dataset:
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+ name: autoevaluate/conll2003-sample
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+ type: autoevaluate/conll2003-sample
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+ config: autoevaluate--conll2003-sample
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  split: test
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  metrics:
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+ - type: accuracy
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+ value: 0.9680247550283652
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+ name: Accuracy
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  verified: true
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+ - type: precision
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+ name: Precision
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  verified: true
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+ - type: 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