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bert-phishing-trainer

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  1. README.md +18 -11
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1372
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- - Accuracy: 0.9699
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- - F1: 0.9693
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- - Precision: 0.9695
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- - Recall: 0.9699
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  ## Model description
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@@ -49,15 +49,22 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 3
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 0.1069 | 1.0 | 2728 | 0.2193 | 0.9558 | 0.9530 | 0.9567 | 0.9558 |
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- | 0.232 | 2.0 | 5456 | 0.1591 | 0.9666 | 0.9654 | 0.9665 | 0.9666 |
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- | 0.0629 | 3.0 | 8184 | 0.1372 | 0.9699 | 0.9693 | 0.9695 | 0.9699 |
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2090
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+ - Accuracy: 0.9467
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+ - F1: 0.9463
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+ - Precision: 0.9469
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+ - Recall: 0.9467
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 10
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.4561 | 1.0 | 1098 | 0.3688 | 0.8738 | 0.8709 | 0.8760 | 0.8738 |
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+ | 0.3126 | 2.0 | 2196 | 0.2254 | 0.9339 | 0.9335 | 0.9340 | 0.9339 |
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+ | 0.3852 | 3.0 | 3294 | 0.3113 | 0.9280 | 0.9274 | 0.9284 | 0.9280 |
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+ | 0.2341 | 4.0 | 4392 | 0.2376 | 0.9417 | 0.9417 | 0.9418 | 0.9417 |
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+ | 0.2108 | 5.0 | 5490 | 0.2433 | 0.9408 | 0.9407 | 0.9407 | 0.9408 |
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+ | 0.0882 | 6.0 | 6588 | 0.2353 | 0.9371 | 0.9364 | 0.9384 | 0.9371 |
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+ | 0.127 | 7.0 | 7686 | 0.2674 | 0.9276 | 0.9270 | 0.9277 | 0.9276 |
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+ | 0.1413 | 8.0 | 8784 | 0.2859 | 0.9339 | 0.9341 | 0.9344 | 0.9339 |
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+ | 0.7061 | 9.0 | 9882 | 0.6121 | 0.6761 | 0.5834 | 0.7861 | 0.6761 |
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+ | 0.2076 | 10.0 | 10980 | 0.2090 | 0.9467 | 0.9463 | 0.9469 | 0.9467 |
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  ### Framework versions
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