---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_keras_callback
model-index:
- name: SIA86/bert-cased-text-classification
  results: []

widget:
- text: "Не могу отправить письмо с электронной почты."
  example_title: "Пример 1"
- text: "Прошу установить AutoCad на мой компьютер."
  example_title: "Пример 2"
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# SIA86/bert-cased-text-classification

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0719
- Train Accuracy: 0.9772
- Validation Loss: 0.8075
- Validation Accuracy: 0.8485
- Epoch: 19

## 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:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 2320, 'end_learning_rate': 0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 2.8423     | 0.2313         | 2.5340          | 0.3593              | 0     |
| 2.4502     | 0.3181         | 2.3051          | 0.3333              | 1     |
| 2.2064     | 0.3648         | 1.9143          | 0.4416              | 2     |
| 1.6431     | 0.5494         | 1.5876          | 0.5411              | 3     |
| 1.1282     | 0.6960         | 1.4404          | 0.6190              | 4     |
| 0.8128     | 0.7861         | 1.0982          | 0.7143              | 5     |
| 0.6016     | 0.8534         | 1.0513          | 0.7532              | 6     |
| 0.4495     | 0.8947         | 0.9108          | 0.7879              | 7     |
| 0.2991     | 0.9414         | 0.8437          | 0.8182              | 8     |
| 0.2068     | 0.9609         | 0.7936          | 0.8182              | 9     |
| 0.1594     | 0.9729         | 0.8264          | 0.8182              | 10    |
| 0.1364     | 0.9707         | 0.7984          | 0.8312              | 11    |
| 0.1217     | 0.9707         | 0.7948          | 0.8268              | 12    |
| 0.1053     | 0.9729         | 0.7847          | 0.8398              | 13    |
| 0.0968     | 0.9729         | 0.7850          | 0.8398              | 14    |
| 0.0879     | 0.9739         | 0.7976          | 0.8442              | 15    |
| 0.0821     | 0.9718         | 0.8005          | 0.8442              | 16    |
| 0.0770     | 0.9750         | 0.7967          | 0.8485              | 17    |
| 0.0772     | 0.9772         | 0.8043          | 0.8485              | 18    |
| 0.0719     | 0.9772         | 0.8075          | 0.8485              | 19    |


### Framework versions

- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.14.1
- Tokenizers 0.13.3