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README.md
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---
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library_name: transformers
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license: apache-2.0
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base_model: distilbert-base-uncased
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tags:
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- text-classification
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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model-index:
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- name: phishing-links-detection-using-transformers
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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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# phishing-links-detection-using-transformers
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the Razvan27/remla_phishing_url dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1545
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- Precision: 0.9757
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- Recall: 0.9673
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- F1: 0.9715
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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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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- distributed_type: tpu
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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: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|
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| 0.1044 | 1.0 | 3269 | 0.0874 | 0.9688 | 0.9583 | 0.9635 |
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| 0.0709 | 2.0 | 6538 | 0.0938 | 0.9603 | 0.9736 | 0.9669 |
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| 0.0224 | 3.0 | 9807 | 0.1064 | 0.9781 | 0.9644 | 0.9712 |
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| 0.0254 | 4.0 | 13076 | 0.1281 | 0.9768 | 0.9653 | 0.9710 |
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| 0.0161 | 5.0 | 16345 | 0.1545 | 0.9757 | 0.9673 | 0.9715 |
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### Framework versions
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- Transformers 4.51.3
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- Pytorch 2.6.0+cpu
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- Tokenizers 0.21.1
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