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nlp-esg-scoring/bert-base-finetuned-esg-gri-clean
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: 1.9511
- Validation Loss: 1.5293
- 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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -797, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'passive_serialization': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 1.9468 | 1.5190 | 0 |
| 1.9433 | 1.5186 | 1 |
| 1.9569 | 1.4843 | 2 |
| 1.9510 | 1.5563 | 3 |
| 1.9451 | 1.5308 | 4 |
| 1.9576 | 1.5209 | 5 |
| 1.9464 | 1.5324 | 6 |
| 1.9525 | 1.5168 | 7 |
| 1.9488 | 1.5340 | 8 |
| 1.9511 | 1.5293 | 9 |
Framework versions
- Transformers 4.20.1
- TensorFlow 2.8.2
- Datasets 2.3.2
- Tokenizers 0.12.1
