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

sourceHugging Faceapache-2.0updated 4y agoView on Hugging Face
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Model Card

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nlp-esg-scoring/bert-base-finetuned-esg-TCFD-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: 2.7816
  • —Validation Loss: 2.3592
  • —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', 'learningrate': {'classname': 'WarmUp', 'config': {'initiallearningrate': 2e-05, 'decayschedulefn': {'classname': 'PolynomialDecay', 'config': {'initiallearningrate': 2e-05, 'decaysteps': -571, 'endlearningrate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '_passiveserialization_': True}, 'warmupsteps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta1': 0.9, 'beta2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weightdecayrate': 0.01}
  • —training_precision: float32

Training results

Train LossValidation LossEpoch
2.77762.36470
2.77442.34691
2.76832.35272
2.77432.37083
2.78092.38194
2.76742.35995
2.77152.35416
2.77662.34237
2.78342.35358
2.78162.35929

Framework versions

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