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Regression_bert_7
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: 0.1702
- Train Mae: 0.2696
- Train Mse: 0.1221
- Train R2-score: 0.7766
- Validation Loss: 0.3290
- Validation Mae: 0.2756
- Validation Mse: 0.1076
- Validation R2-score: 0.8214
- Epoch: 9
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': 1e-04, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Train Mae | Train Mse | Train R2-score | Validation Loss | Validation Mae | Validation Mse | Validation R2-score | Epoch |
|---|---|---|---|---|---|---|---|---|
| 0.5303 | 0.3176 | 0.1540 | 0.7493 | 0.6752 | 0.3537 | 0.1857 | 0.6758 | 0 |
| 0.2316 | 0.2775 | 0.1261 | 0.7746 | 0.2451 | 0.3060 | 0.1466 | 0.7473 | 1 |
| 0.2780 | 0.2930 | 0.1373 | 0.8061 | 0.1807 | 0.2593 | 0.1127 | 0.8102 | 2 |
| 0.1776 | 0.2673 | 0.1177 | 0.6536 | 0.1407 | 0.2617 | 0.1181 | 0.7975 | 3 |
| 0.2248 | 0.2906 | 0.1349 | 0.7639 | 0.1896 | 0.2915 | 0.1364 | 0.7665 | 4 |
| 0.2295 | 0.2718 | 0.1196 | 0.7991 | 0.2038 | 0.2757 | 0.1248 | 0.7882 | 5 |
| 0.2443 | 0.2460 | 0.0975 | 0.7298 | 0.1509 | 0.2779 | 0.1301 | 0.7783 | 6 |
| 0.2538 | 0.2907 | 0.1343 | 0.7783 | 0.1930 | 0.2984 | 0.1426 | 0.7559 | 7 |
| 0.2067 | 0.2777 | 0.1281 | 0.7605 | 0.1537 | 0.2809 | 0.1318 | 0.7756 | 8 |
| 0.1702 | 0.2696 | 0.1221 | 0.7766 | 0.3290 | 0.2756 | 0.1076 | 0.8214 | 9 |
Framework versions
- Transformers 4.27.3
- TensorFlow 2.11.0
- Datasets 2.10.1
- Tokenizers 0.13.2
