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metadata
license: apache-2.0
tags:
  - generated_from_keras_callback
model-index:
  - name: silviacamplani/distilbert-finetuned-ner-music
    results: []

silviacamplani/distilbert-finetuned-ner-music

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: 1.1390
  • Validation Loss: 1.0990
  • Train Precision: 0.4018
  • Train Recall: 0.4527
  • Train F1: 0.4257
  • Train Accuracy: 0.7181
  • Epoch: 3

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': 1e-05, 'decay_steps': 370, '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
2.6671 2.0032 0.0 0.0 0.0 0.5482 0
1.7401 1.5194 0.1820 0.0693 0.1004 0.5902 1
1.3487 1.2627 0.2628 0.2952 0.2781 0.6766 2
1.1390 1.0990 0.4018 0.4527 0.4257 0.7181 3

Framework versions

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