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---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_keras_callback
model-index:
- name: ru_propaganda_opposition_model_bert-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_bert-base-multilingual-cased
This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0004
- Validation Loss: 0.2406
- 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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 7695, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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 |
|:----------:|:---------------:|:--------------:|:-----:|
| 0.2769 | 0.1252 | 0.9474 | 0 |
| 0.0922 | 0.1174 | 0.9573 | 1 |
| 0.0506 | 0.1379 | 0.9507 | 2 |
| 0.0280 | 0.1858 | 0.9463 | 3 |
| 0.0204 | 0.1518 | 0.9584 | 4 |
| 0.0148 | 0.1745 | 0.9496 | 5 |
| 0.0091 | 0.2365 | 0.9419 | 6 |
| 0.0054 | 0.1793 | 0.9606 | 7 |
| 0.0057 | 0.1874 | 0.9595 | 8 |
| 0.0032 | 0.2165 | 0.9540 | 9 |
| 0.0020 | 0.6815 | 0.8970 | 10 |
| 0.0061 | 0.2158 | 0.9496 | 11 |
| 0.0007 | 0.2652 | 0.9452 | 12 |
| 0.0002 | 0.2304 | 0.9595 | 13 |
| 0.0004 | 0.2406 | 0.9551 | 14 |
### Framework versions
- Transformers 4.44.2
- TensorFlow 2.17.0
- Datasets 3.1.0
- Tokenizers 0.19.1
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