End of training

README.md

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+---
+license: mit
+base_model: prajjwal1/bert-small
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: bert-small-phishing
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# bert-small-phishing
+
+This model is a fine-tuned version of [prajjwal1/bert-small](https://huggingface.co/prajjwal1/bert-small) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1006
+- Accuracy: 0.9766
+- Precision: 0.9713
+- Recall: 0.9669
+- F1: 0.9691
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.202         | 1.0   | 762  | 0.0941          | 0.9717   | 0.9728    | 0.9520 | 0.9623 |
+| 0.077         | 2.0   | 1524 | 0.0964          | 0.9764   | 0.9757    | 0.9617 | 0.9686 |
+| 0.0428        | 3.0   | 2286 | 0.0992          | 0.9786   | 0.9739    | 0.9695 | 0.9717 |
+| 0.0248        | 4.0   | 3048 | 0.1006          | 0.9766   | 0.9713    | 0.9669 | 0.9691 |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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