silviacamplani/distilbert-base-uncased-finetuned-dapt-ner-ai_data

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

  • Train Loss: 2.3549
  • Validation Loss: 2.3081
  • Train Precision: 0.0
  • Train Recall: 0.0
  • Train F1: 0.0
  • Train Accuracy: 0.6392
  • Epoch: 2

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: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 18, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
  • training_precision: mixed_float16

Training results

Train Loss Validation Loss Train Precision Train Recall Train F1 Train Accuracy Epoch
3.0905 2.8512 0.0 0.0 0.0 0.6376 0
2.6612 2.4783 0.0 0.0 0.0 0.6392 1
2.3549 2.3081 0.0 0.0 0.0 0.6392 2

Framework versions

  • Transformers 4.20.1
  • TensorFlow 2.6.4
  • Datasets 2.1.0
  • Tokenizers 0.12.1
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