arthur-neto/summarization_fine_tune_bbc_summary

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: 0.4118
• Validation Loss: 0.3121
• Train Lr: 2e-05
• 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': np.float32(2e-05), 'decay': 0.0, 'beta_1': np.float32(0.9), 'beta_2': np.float32(0.999), 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
• training_precision: float32

Training results

Train Loss	Validation Loss	Train Lr	Epoch
1.4265	0.5026	2e-05	0
0.5826	0.3627	2e-05	1
0.4576	0.3325	2e-05	2
0.4118	0.3121	2e-05	3

Framework versions

• Transformers 4.57.1
• TensorFlow 2.19.0
• Datasets 4.0.0
• Tokenizers 0.22.1