---
library_name: transformers
base_model: DeepPavlov/rubert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: learn_hf_phishing_not_phishing_text_classifier
  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. -->

# learn_hf_phishing_not_phishing_text_classifier

This model is a fine-tuned version of [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0943
- Accuracy: 0.9796

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5017        | 1.0   | 7    | 0.4998          | 0.8367   |
| 0.275         | 2.0   | 14   | 0.0606          | 0.9796   |
| 0.0377        | 3.0   | 21   | 0.0091          | 1.0      |
| 0.0408        | 4.0   | 28   | 0.0078          | 1.0      |
| 0.0013        | 5.0   | 35   | 0.0117          | 1.0      |
| 0.0007        | 6.0   | 42   | 0.0678          | 0.9796   |
| 0.0005        | 7.0   | 49   | 0.0906          | 0.9796   |
| 0.0004        | 8.0   | 56   | 0.0987          | 0.9796   |
| 0.0004        | 9.0   | 63   | 0.1012          | 0.9796   |
| 0.0004        | 10.0  | 70   | 0.0943          | 0.9796   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0