---
license: apache-2.0
tags:
- generated_from_keras_callback
model-index:
- name: ru_propaganda_opposition_model_distilbert-base-multilingual-cased
  results: []
---

<!-- 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. -->

# ru_propaganda_opposition_model_distilbert-base-multilingual-cased

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0003
- Validation Loss: 0.2582
- Train Accuracy: 0.9551
- Epoch: 14

## 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': 2e-05, 'decay_steps': 7695, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Accuracy | Epoch |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.2994     | 0.2306          | 0.9091         | 0     |
| 0.1127     | 0.1394          | 0.9540         | 1     |
| 0.0485     | 0.1417          | 0.9485         | 2     |
| 0.0256     | 0.1394          | 0.9562         | 3     |
| 0.0158     | 0.1835          | 0.9617         | 4     |
| 0.0106     | 0.1984          | 0.9617         | 5     |
| 0.0082     | 0.2812          | 0.9376         | 6     |
| 0.0030     | 0.2452          | 0.9562         | 7     |
| 0.0033     | 0.2022          | 0.9595         | 8     |
| 0.0052     | 0.2328          | 0.9529         | 9     |
| 0.0022     | 0.2302          | 0.9573         | 10    |
| 0.0019     | 0.2552          | 0.9529         | 11    |
| 0.0019     | 0.2461          | 0.9584         | 12    |
| 0.0006     | 0.2569          | 0.9551         | 13    |
| 0.0003     | 0.2582          | 0.9551         | 14    |


### Framework versions

- Transformers 4.29.1
- TensorFlow 2.12.0
- Datasets 2.12.0
- Tokenizers 0.13.3