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hasan-mr/t5-small-finetuned-summarization-billsum
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: 2.5791
- Validation Loss: 2.3660
- Train Rougel: tf.Tensor(0.129898, shape=(), dtype=float32)
- Epoch: 3
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': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: mixed_float16
Training results
| Train Loss | Validation Loss | Train Rougel | Epoch |
|---|---|---|---|
| 3.3746 | 2.7009 | tf.Tensor(0.10603927, shape=(), dtype=float32) | 0 |
| 2.8289 | 2.5104 | tf.Tensor(0.108828835, shape=(), dtype=float32) | 1 |
| 2.6672 | 2.4200 | tf.Tensor(0.1210279, shape=(), dtype=float32) | 2 |
| 2.5791 | 2.3660 | tf.Tensor(0.129898, shape=(), dtype=float32) | 3 |
Framework versions
- Transformers 4.34.0
- TensorFlow 2.14.0
- Datasets 2.14.5
- Tokenizers 0.14.1
