<!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. -->
hasan-mr/t5-small-finetuned-summarization-billsum-v1
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: 2.5716
- Validation Loss: 2.3842
- Train Rougel: tf.Tensor(0.13416424, 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 |
|---|---|---|---|
| 3.3695 | 2.7228 | tf.Tensor(0.10740497, shape=(), dtype=float32) | 0 |
| 2.8189 | 2.5337 | tf.Tensor(0.11091911, shape=(), dtype=float32) | 1 |
| 2.6657 | 2.4427 | tf.Tensor(0.124923535, shape=(), dtype=float32) | 2 |
| 2.5716 | 2.3842 | tf.Tensor(0.13416424, shape=(), dtype=float32) | 3 |
Framework versions
- Transformers 4.34.0
- TensorFlow 2.14.0
- Datasets 2.14.5
- Tokenizers 0.14.1
