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ru_propaganda_opposition_model_bert-base-multilingual-cased

This model is a fine-tuned version of 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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