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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
