T5-Finetuned-legal_summarization

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:
• Validation Loss:
• Train Rougel: tf.Tensor(0.21532206, shape=(), dtype=float32)
• Epoch:

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': 1e-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
		tf.Tensor(0.21532206, shape=(), dtype=float32)

Framework versions

• Transformers 4.20.0
• TensorFlow 2.12.0
• Datasets 2.12.0
• Tokenizers 0.12.1