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Perfect7613
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modernbert-phishing-classifier

Text Classification
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Safetensors
modernbert
Generated from Trainer
text-embeddings-inference
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End of training

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  1. README.md +18 -13
  2. model.safetensors +1 -1
  3. runs/Mar17_16-28-27_43e3db9356a5/events.out.tfevents.1742228917.43e3db9356a5.1316.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2743
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- - Accuracy: 0.893
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  - Auc: 0.965
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  ## Model description
@@ -45,22 +45,27 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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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 | Auc |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|
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- | 0.356 | 1.0 | 263 | 0.2760 | 0.869 | 0.953 |
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- | 0.2567 | 2.0 | 526 | 0.2714 | 0.882 | 0.961 |
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- | 0.2343 | 3.0 | 789 | 0.2607 | 0.891 | 0.962 |
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- | 0.2047 | 4.0 | 1052 | 0.2652 | 0.893 | 0.963 |
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- | 0.1999 | 5.0 | 1315 | 0.3361 | 0.893 | 0.962 |
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- | 0.1828 | 6.0 | 1578 | 0.2679 | 0.902 | 0.964 |
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- | 0.1703 | 7.0 | 1841 | 0.2720 | 0.9 | 0.965 |
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- | 0.1614 | 8.0 | 2104 | 0.2750 | 0.896 | 0.965 |
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- | 0.1575 | 9.0 | 2367 | 0.2752 | 0.893 | 0.965 |
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- | 0.1524 | 10.0 | 2630 | 0.2743 | 0.893 | 0.965 |
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3066
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+ - Accuracy: 0.9
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  - Auc: 0.965
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  ## Model description
 
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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+ - num_epochs: 15
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|
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+ | 0.3714 | 1.0 | 263 | 0.2936 | 0.869 | 0.949 |
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+ | 0.2622 | 2.0 | 526 | 0.2681 | 0.884 | 0.96 |
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+ | 0.2405 | 3.0 | 789 | 0.2642 | 0.898 | 0.961 |
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+ | 0.2091 | 4.0 | 1052 | 0.2688 | 0.893 | 0.963 |
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+ | 0.2078 | 5.0 | 1315 | 0.3813 | 0.882 | 0.962 |
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+ | 0.1887 | 6.0 | 1578 | 0.2667 | 0.9 | 0.965 |
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+ | 0.1695 | 7.0 | 1841 | 0.2851 | 0.902 | 0.964 |
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+ | 0.1654 | 8.0 | 2104 | 0.2935 | 0.902 | 0.964 |
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+ | 0.157 | 9.0 | 2367 | 0.3169 | 0.904 | 0.966 |
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+ | 0.158 | 10.0 | 2630 | 0.3190 | 0.896 | 0.964 |
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+ | 0.149 | 11.0 | 2893 | 0.3019 | 0.893 | 0.965 |
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+ | 0.1437 | 12.0 | 3156 | 0.2995 | 0.9 | 0.965 |
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+ | 0.1365 | 13.0 | 3419 | 0.3048 | 0.9 | 0.965 |
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+ | 0.1312 | 14.0 | 3682 | 0.3090 | 0.898 | 0.965 |
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+ | 0.1304 | 15.0 | 3945 | 0.3066 | 0.9 | 0.965 |
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  ### Framework versions
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