---
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_rubert
  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_rubert

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: 0.1041
- Accuracy: 0.9870

## 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 OptimizerNames.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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5787        | 1.0   | 10   | 0.2982          | 0.9610   |
| 0.1417        | 2.0   | 20   | 0.1449          | 0.9610   |
| 0.0454        | 3.0   | 30   | 0.0945          | 0.9870   |
| 0.1515        | 4.0   | 40   | 0.2828          | 0.9610   |
| 0.0611        | 5.0   | 50   | 0.0820          | 0.9870   |
| 0.0018        | 6.0   | 60   | 0.0945          | 0.9870   |
| 0.0033        | 7.0   | 70   | 0.0998          | 0.9870   |
| 0.0006        | 8.0   | 80   | 0.1025          | 0.9870   |
| 0.0005        | 9.0   | 90   | 0.1037          | 0.9870   |
| 0.0004        | 10.0  | 100  | 0.1041          | 0.9870   |


### Framework versions

- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1