reward-opi-reddit
This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0439
- Train Accuracy: 0.9907
- Validation Loss: 3.5663
- Validation Accuracy: 0.5521
- Epoch: 4
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': 2e-05, '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 |
---|---|---|---|---|
0.0177 | 0.9950 | 3.9631 | 0.5521 | 0 |
0.0422 | 0.9860 | 3.8653 | 0.5521 | 1 |
0.0392 | 0.9928 | 2.6393 | 0.5521 | 2 |
0.1300 | 0.9659 | 3.7265 | 0.5521 | 3 |
0.0439 | 0.9907 | 3.5663 | 0.5521 | 4 |
Framework versions
- Transformers 4.36.1
- TensorFlow 2.15.0
- Tokenizers 0.15.2
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