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minhnb/distilbert-base-uncased-finetuned-stsb
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.8850
- Validation Loss: 1.0628
- Train Pearson: -0.8141
- Train Spearmanr: -0.8001
- Epoch: 2
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': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1077, '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 Pearson | Train Spearmanr | Epoch |
|---|---|---|---|---|
| 1.3834 | 1.1223 | -0.8324 | -0.8200 | 0 |
| 1.0416 | 1.0734 | -0.8086 | -0.7989 | 1 |
| 0.8850 | 1.0628 | -0.8141 | -0.8001 | 2 |
Framework versions
- Transformers 4.34.1
- TensorFlow 2.14.0
- Datasets 2.14.6
- Tokenizers 0.14.1
