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JuvManga-87/mobilebert-uncased-finetuned-ner

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

  • Train Loss: 0.2691
  • Validation Loss: 0.2428
  • Train Precision: 0.6071
  • Train Recall: 0.0424
  • Train F1: 0.0793
  • Train Accuracy: 0.9240
  • Epoch: 11

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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 264, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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 Train Precision Train Recall Train F1 Train Accuracy Epoch
1.2686 0.5142 0.0187 0.0125 0.0149 0.8729 0
0.4703 0.4127 0.02 0.0050 0.0080 0.9031 1
0.4033 0.3659 0.0588 0.0050 0.0092 0.9156 2
0.3657 0.3351 0.1429 0.0050 0.0096 0.9195 3
0.3434 0.3111 0.2143 0.0075 0.0145 0.9199 4
0.3223 0.2917 0.2667 0.0100 0.0192 0.9203 5
0.3035 0.2764 0.3125 0.0125 0.0240 0.9209 6
0.2916 0.2642 0.5294 0.0224 0.0431 0.9224 7
0.2780 0.2551 0.4762 0.0249 0.0474 0.9226 8
0.2755 0.2484 0.56 0.0349 0.0657 0.9234 9
0.2718 0.2442 0.6071 0.0424 0.0793 0.9240 10
0.2691 0.2428 0.6071 0.0424 0.0793 0.9240 11

Framework versions

  • Transformers 4.42.4
  • TensorFlow 2.17.0
  • Datasets 2.21.0
  • Tokenizers 0.19.1
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