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krm/mt5-small-OrangeSum-Summarizer
This model is a fine-tuned version of google/mt5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 3.7771
- Validation Loss: 2.5727
- 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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5.6e-05, 'decay_steps': 5000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: mixed_float16
Training results
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 7.8346 | 3.2199 | 0 |
| 5.1020 | 2.8619 | 1 |
| 4.5632 | 2.7564 | 2 |
| 4.2564 | 2.6726 | 3 |
| 4.0501 | 2.6300 | 4 |
| 3.9185 | 2.5930 | 5 |
| 3.8209 | 2.5792 | 6 |
| 3.7771 | 2.5727 | 7 |
Framework versions
- Transformers 4.22.2
- TensorFlow 2.8.2
- Datasets 2.5.2
- Tokenizers 0.12.1
