IntelDAOS5Classic_Train_Balance_DATA_ratio_4

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: 0.4963
  • Train Accuracy: 0.7982
  • Validation Loss: 0.5228
  • Validation Accuracy: 0.8050
  • 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: {'name': 'Adam', 'weight_decay': None, 'clipnorm': 1.0, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': 3e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Train Accuracy Validation Loss Validation Accuracy Epoch
0.5191 0.7843 0.4927 0.8050 0
0.5012 0.7982 0.4909 0.8050 1
0.4963 0.7982 0.5228 0.8050 2

Framework versions

  • Transformers 4.29.2
  • TensorFlow 2.12.0
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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