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Thangnv/my_t5

This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 0.4858
  • Train Sparse Categorical Accuracy: 0.8583
  • Validation Loss: 0.4856
  • Validation Sparse Categorical Accuracy: 0.8604
  • 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': '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': 0.001, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Train Sparse Categorical Accuracy Validation Loss Validation Sparse Categorical Accuracy Epoch
0.7764 0.7851 0.6316 0.8233 0
0.6144 0.8267 0.5740 0.8381 1
0.5726 0.8371 0.5442 0.8455 2
0.5483 0.8431 0.5273 0.8501 3
0.5315 0.8472 0.5156 0.8527 4
0.5187 0.8503 0.5060 0.8554 5
0.5083 0.8529 0.4995 0.8572 6
0.4997 0.8549 0.4955 0.8581 7
0.4923 0.8567 0.4895 0.8596 8
0.4858 0.8583 0.4856 0.8604 9

Framework versions

  • Transformers 4.33.2
  • TensorFlow 2.13.0
  • Datasets 2.14.5
  • Tokenizers 0.13.3
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