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Upload DebertaV2ForSequenceClassification

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  1. README.md +4 -4
  2. config.json +1 -1
README.md CHANGED
@@ -2,10 +2,10 @@
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  language:
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  - en
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  license: mit
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- base_model: microsoft/deberta-v2-xlarge
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  tags:
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  - nycu-112-2-datamining-hw2
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  - generated_from_trainer
 
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  datasets:
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  - DandinPower/review_onlytitleandtext
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  metrics:
@@ -14,15 +14,15 @@ model-index:
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  - name: deberta-v2-xlarge-otat-recommened-hp
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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: DandinPower/review_onlytitleandtext
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  type: DandinPower/review_onlytitleandtext
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  metrics:
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- - name: Accuracy
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- type: accuracy
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  value: 0.6777142857142857
 
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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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  language:
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  - en
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  license: mit
 
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  tags:
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  - nycu-112-2-datamining-hw2
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  - generated_from_trainer
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+ base_model: microsoft/deberta-v2-xlarge
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  datasets:
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  - DandinPower/review_onlytitleandtext
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  metrics:
 
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  - name: deberta-v2-xlarge-otat-recommened-hp
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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: DandinPower/review_onlytitleandtext
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  type: DandinPower/review_onlytitleandtext
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  metrics:
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+ - type: accuracy
 
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  value: 0.6777142857142857
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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
config.json CHANGED
@@ -1,5 +1,5 @@
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  {
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- "_name_or_path": "microsoft/deberta-v2-xlarge",
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  "architectures": [
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  "DebertaV2ForSequenceClassification"
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  ],
 
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  {
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+ "_name_or_path": "/mnt/nvme3n1p1/text-classification-exp/deberta-v2-xlarge-otat-recommened-hp/checkpoint-1500",
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  "architectures": [
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  "DebertaV2ForSequenceClassification"
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  ],