flan-t5-base-text_summarization_data

This model is a fine-tuned version of google/flan-t5-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.7386
• Rouge1: 43.6615
• Rouge2: 20.349
• Rougel: 40.1032
• Rougelsum: 40.1589
• Gen Len: 14.6434

Model description

This is a text summarization model.

For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Text%20Summarization/Text-Summarized%20Data%20-%20Comparison/Flan-T5%20-%20Text%20Summarization%20-%201%20Epoch.ipynb

Intended uses & limitations

This model is intended to demonstrate my ability to solve a complex problem using technology.

Training and evaluation data

Dataset Source: https://www.kaggle.com/datasets/cuitengfeui/textsummarization-data

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.0287	1.0	1197	1.7386	43.6615	20.349	40.1032	40.1589	14.6434

Framework versions

• Transformers 4.26.1
• Pytorch 1.12.1
• Datasets 2.9.0
• Tokenizers 0.12.1