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lmchion/distilbert-finetuned-esg-a4s

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 2.2859
  • Validation Loss: 2.3354
  • 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
2.8805 2.7153 0
2.6414 2.5472 1
2.5202 2.4813 2
2.4306 2.3834 3
2.3452 2.3297 4
2.2940 2.3201 5
2.2889 2.3061 6
2.2726 2.3471 7
2.2827 2.3432 8
2.2859 2.3354 9

Framework versions

  • Transformers 4.20.0
  • TensorFlow 2.8.2
  • Datasets 2.3.2
  • Tokenizers 0.12.1
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