nlp-esg-scoring/bert-base-finetuned-esg-a4s

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 1.9437
• Validation Loss: 1.9842
• 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': -812, '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
1.9200	2.0096	0
1.9249	1.9926	1
1.9366	2.0100	2
1.9327	1.9814	3
1.9266	2.0152	4
1.9332	2.0519	5
1.9203	2.0437	6
1.9238	2.0118	7
1.9290	2.0019	8
1.9437	1.9842	9

Framework versions

• Transformers 4.20.1
• TensorFlow 2.8.2
• Datasets 2.3.2
• Tokenizers 0.12.1