A running version of the model is hosted on Huggingface.

Collection of Jupyter Notebooks focusing on the fine-tuning of T5 for text summarization and title generation. The idea is to generate a summary short enough to be a possible title. A version of the fine-tuned model is hosted on Huggingface and can be tested directly from the browser (hosted inference API). The fine-tuned model can be downloaded and used through the Huggingface API.

This model is a fine-tuned version of t5-small on CShorten/ML-ArXiv-Papers.

It achieves the following results on the evaluation set:

• Train Loss: 1.9469
• Train Lr: 0.0004
• Validation Loss: 1.8462
• Validation Lr: 0.0002

The following hyperparameters were used during training:

• optimizer: {'name': 'Adam', 'learning_rate': 0.00015378147, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
• training_precision: float32

• Transformers 4.21.3
• TensorFlow 2.10.0
• Datasets 2.4.0
• Tokenizers 0.12.1