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