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metadata
license: apache-2.0
base_model: bert-base-uncased
tags:
  - generated_from_keras_callback
model-index:
  - name: cc-01-bert-finetuned
    results: []

cc-01-bert-finetuned

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: 0.0058
  • Validation Loss: 0.5378
  • Train Recall: 0.8693
  • Epoch: 7

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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1770, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Validation Loss Train Recall Epoch
0.4422 0.4857 0.9477 0
0.2513 0.3470 0.8497 1
0.1331 0.4266 0.7974 2
0.0640 0.4452 0.8824 3
0.0339 0.5141 0.8366 4
0.0225 0.5295 0.8431 5
0.0090 0.5200 0.8889 6
0.0058 0.5378 0.8693 7

Framework versions

  • Transformers 4.31.0
  • TensorFlow 2.13.0
  • Datasets 2.14.4
  • Tokenizers 0.13.3