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@@ -3,19 +3,23 @@ license: apache-2.0
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  base_model: bert-base-uncased
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  tags:
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  - generated_from_trainer
 
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  metrics:
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  - accuracy
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  model-index:
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  - name: bert-base-uncased-e_CARE
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  results: []
 
 
 
 
 
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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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- should probably proofread and complete it, then remove this comment. -->
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-
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  # bert-base-uncased-e_CARE
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- This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
 
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  It achieves the following results on the evaluation set:
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  - Loss: 1.7677
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  - Accuracy: 0.7212
@@ -55,10 +59,9 @@ The following hyperparameters were used during training:
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  | 0.0212 | 4.0 | 6284 | 1.8194 | 0.7225 |
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  | 0.0185 | 5.0 | 7855 | 1.7677 | 0.7212 |
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-
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  ### Framework versions
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  - Transformers 4.31.0
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.14.2
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- - Tokenizers 0.13.3
 
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  base_model: bert-base-uncased
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  tags:
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  - generated_from_trainer
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+ - Multiple Choice
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  metrics:
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  - accuracy
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  model-index:
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  - name: bert-base-uncased-e_CARE
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  results: []
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+ datasets:
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+ - 12ml/e-CARE
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+ language:
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+ - en
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+ pipeline_tag: question-answering
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  ---
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  # bert-base-uncased-e_CARE
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+ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased).
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+
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  It achieves the following results on the evaluation set:
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  - Loss: 1.7677
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  - Accuracy: 0.7212
 
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  | 0.0212 | 4.0 | 6284 | 1.8194 | 0.7225 |
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  | 0.0185 | 5.0 | 7855 | 1.7677 | 0.7212 |
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  ### Framework versions
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  - Transformers 4.31.0
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.14.2
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+ - Tokenizers 0.13.3