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ru_propaganda_opposition_model_distilbert-base-multilingual-cased
This model is a fine-tuned version of 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
