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README.md
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- generated_from_trainer
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datasets:
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- glue
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metrics:
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- accuracy
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model-index:
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- name: autoevaluate-binary-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: glue
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type: glue
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args: sst2
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metrics:
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- type: accuracy
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value: 0.8967889908256881
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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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dataset:
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name: glue
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type: glue
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config: sst2
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split: validation
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metrics:
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- type: accuracy
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value: 0.8967889908256881
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name: Accuracy
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verified: true
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verifyToken: >-
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- type: precision
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value: 0.8898678414096917
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name: Precision
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verified: true
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verifyToken: >-
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- type: recall
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value: 0.9099099099099099
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name: Recall
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verified: true
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verifyToken: >-
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- type: auc
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value: 0.9672186789593331
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name: AUC
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verified: true
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- type: f1
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value: 0.8997772828507795
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name: F1
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verified: true
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- type: loss
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value: 0.30092036724090576
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name: loss
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verified: true
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- type: matthews_correlation
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value: 0.793630584795814
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name: matthews_correlation
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verified: true
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verifyToken: >-
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duplicated_from: autoevaluate/binary-classification
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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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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3009
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- Accuracy: 0.8968
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- generated_from_trainer
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datasets:
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- glue
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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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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3009
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- Accuracy: 0.8968
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