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metadata
language:
  - en
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - rouge
pipeline_tag: summarization
base_model: google/flan-t5-base
model-index:
  - name: flan-t5-base-text_summarization_data
    results: []

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