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@@ -5,23 +5,23 @@ tags:
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  metrics:
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  - accuracy
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  model-index:
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- - name: my_awesome_model
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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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- # my_awesome_model
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- This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.1140
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  - Accuracy: 0.9750
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  ## Model description
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- More information needed
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  ## Intended uses & limitations
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  metrics:
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  - accuracy
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  model-index:
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+ - name: domain_classification
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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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+ # Domain classification model
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the Opus dataset with IT, medical, law domain.They are extracted from OPUS dataset in english.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.1140
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  - Accuracy: 0.9750
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  ## Model description
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+ The model will classify sentence which belongs to its domain.
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  ## Intended uses & limitations
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