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nlp-esg-scoring/bert-base-finetuned-esg-snpcsr-clean

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

  • Train Loss: 2.4074
  • Validation Loss: 2.2353
  • 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': 1064, '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
2.4095 2.2167 0
2.4085 2.2081 1
2.4117 2.2194 2
2.4127 2.2173 3
2.4063 2.2011 4
2.4114 2.2102 5
2.4177 2.2123 6
2.4102 2.2174 7
2.4096 2.2211 8
2.4074 2.2353 9

Framework versions

  • Transformers 4.20.1
  • TensorFlow 2.8.2
  • Datasets 2.4.0
  • Tokenizers 0.12.1
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