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---
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](https://huggingface.co/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 |