runningsnake/bert-base-sequence-classification
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0825
- Train Accuracy: 0.9766
- Validation Loss: 0.5064
- Validation Accuracy: 0.8431
- Epoch: 2
Model description
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Intended uses & limitations
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How to use
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Limitations and bias
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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': 5e-05, 'decay_steps': 1377, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, '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 |
---|---|---|---|---|
0.2559 | 0.9057 | 0.5082 | 0.8211 | 0 |
0.1004 | 0.9673 | 0.5064 | 0.8431 | 1 |
0.0825 | 0.9766 | 0.5064 | 0.8431 | 2 |
Framework versions
- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.14.0
- Tokenizers 0.13.3
Evaluation results
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Model tree for runningsnake/bert-base-sequence-classification
Base model
google-bert/bert-base-uncased