DeepNeural/text-summarization-model-t5

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