metadata
library_name: transformers
license: apache-2.0
base_model: t5-small
tags:
- generated_from_keras_callback
model-index:
- name: transformers-med-summarizer
results: []
transformers-med-summarizer
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: 2.4154
- 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