| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: t5-small |
| tags: |
| - generated_from_keras_callback |
| model-index: |
| - name: transformers-med-summarizer |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # transformers-med-summarizer |
|
|
| This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Train Loss: 2.4154 |
| - Validation Loss: 2.2092 |
| - Train Rougel: tf.Tensor(0.12209402, shape=(), dtype=float32) |
| - Epoch: 1 |
|
|
| ## 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': np.float32(2e-05), 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False} |
| - training_precision: float32 |
| |
| ### Training results |
| |
| | Train Loss | Validation Loss | Train Rougel | Epoch | |
| |:----------:|:---------------:|:----------------------------------------------:|:-----:| |
| | 2.6063 | 2.2850 | tf.Tensor(0.12259579, shape=(), dtype=float32) | 0 | |
| | 2.4154 | 2.2092 | tf.Tensor(0.12209402, shape=(), dtype=float32) | 1 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.51.3 |
| - TensorFlow 2.18.0 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.1 |
| |
