Model save

README.md

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+---
+license: apache-2.0
+base_model: bert-large-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: phishing_3_1
+  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. -->
+
+# phishing_3_1
+
+This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5678
+- Accuracy: 0.9837
+- Precision: 0.9884
+- Recall: 0.9788
+- False Positive Rate: 0.0115
+
+## 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: 12
+- eval_batch_size: 12
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | False Positive Rate |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:-------------------:|
+| 0.5925        | 1.0   | 3025  | 0.5767          | 0.9743   | 0.9853    | 0.9630 | 0.0143              |
+| 0.5784        | 2.0   | 6050  | 0.5709          | 0.9802   | 0.9764    | 0.9841 | 0.0238              |
+| 0.5766        | 3.0   | 9075  | 0.6025          | 0.9490   | 0.9968    | 0.9008 | 0.0029              |
+| 0.5682        | 4.0   | 12100 | 0.5678          | 0.9837   | 0.9884    | 0.9788 | 0.0115              |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2