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metadata
license: apache-2.0
tags:
  - generated_from_keras_callback
base_model: bert-base-uncased
model-index:
  - name: nlp-esg-scoring/bert-base-finetuned-esg-gri-clean
    results: []

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