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Training in progress epoch 9
dface85
metadata
base_model: bert-base-chinese
tags:
  - generated_from_keras_callback
model-index:
  - name: Mattis0525/bert-base-chinese-finetuned-tcfd
    results: []

Mattis0525/bert-base-chinese-finetuned-tcfd

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

  • Train Loss: 0.6502
  • Train Accuracy: 0.0591
  • Validation Loss: 0.6504
  • Validation Accuracy: 0.0591
  • 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': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -800, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, '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 Train Accuracy Validation Loss Validation Accuracy Epoch
0.9480 0.0555 0.8742 0.0566 0
0.8735 0.0567 0.7660 0.0589 1
0.7694 0.0574 0.7093 0.0584 2
0.7190 0.0588 0.6563 0.0604 3
0.6720 0.0592 0.6636 0.0601 4
0.6479 0.0596 0.6639 0.0602 5
0.6446 0.0598 0.6266 0.0614 6
0.6257 0.0602 0.6393 0.0609 7
0.6534 0.0590 0.6301 0.0588 8
0.6502 0.0591 0.6504 0.0591 9

Framework versions

  • Transformers 4.41.1
  • TensorFlow 2.15.0
  • Datasets 2.19.1
  • Tokenizers 0.19.1