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@@ -15,6 +15,7 @@ This is the model card of a 🤗 transformers model that has been pushed on the
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  This model is modified version of distilbert/distilbert-base-uncased trained via knowledge distillation from shawhin/bert-phishing-classifier_teacher using the shawhin/phishing-site-classification dataset. It achieves the following results on the testing set:
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  Loss (training): 0.0673365443944931
 
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  Accuracy: 0.9089
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  Precision: 0.8950
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  Recall: 0.9301
@@ -110,6 +111,8 @@ num_epochs: 5
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  temperature: 2.0
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  adam optimizer alpha: 0.5
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  - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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  #### Speeds, Sizes, Times [optional]
 
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  This model is modified version of distilbert/distilbert-base-uncased trained via knowledge distillation from shawhin/bert-phishing-classifier_teacher using the shawhin/phishing-site-classification dataset. It achieves the following results on the testing set:
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  Loss (training): 0.0673365443944931
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  Accuracy: 0.9089
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  Precision: 0.8950
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  Recall: 0.9301
 
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  temperature: 2.0
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  adam optimizer alpha: 0.5
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  - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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  #### Speeds, Sizes, Times [optional]