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--- |
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license: apache-2.0 |
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tags: |
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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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- matched_accuracy |
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- missmatched_accuracy |
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model-index: |
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- name: deberta-v3-base-finetuned-MNLI |
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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: glue |
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type: glue |
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args: mnli |
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metrics: |
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- name: Matched Accuracy |
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type: matched_accuracy |
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value: 0.9056546102903719 |
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- name: Missmatched Accuracy |
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type: missmatched_accuracy |
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value: 0.9104963384865744 |
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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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# deberta-v3-base-finetuned-mnli |
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This model is a fine-tuned version of [deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the glue dataset. |
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It achieves the following results on the evaluation set: |
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- Matched Accuracy: 0.9057 |
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- Missmatched Accuracy: 0.9105 |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- weight_decay: 0.01 |
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- num_epochs: 2 |
