---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: flan-T5-base-sum
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: samsum
      type: samsum
      config: samsum
      split: test
      args: samsum
    metrics:
    - name: Rouge1
      type: rouge
      value: 47.6617
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# flan-T5-base-sum

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3721
- Rouge1: 47.6617
- Rouge2: 23.7647
- Rougel: 40.1155
- Rougelsum: 43.6943
- Gen Len: 17.2759

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.4403        | 1.0   | 1842 | 1.3822          | 47.2814 | 23.7835 | 39.7427 | 43.4897   | 17.0256 |
| 1.3572        | 2.0   | 3684 | 1.3747          | 47.553  | 23.5714 | 39.8212 | 43.6246   | 17.4420 |
| 1.2822        | 3.0   | 5526 | 1.3721          | 47.6617 | 23.7647 | 40.1155 | 43.6943   | 17.2759 |
| 1.2375        | 4.0   | 7368 | 1.3764          | 47.7453 | 24.1099 | 40.1684 | 43.8659   | 17.2943 |
| 1.1935        | 5.0   | 9210 | 1.3780          | 47.614  | 23.6643 | 39.8434 | 43.6558   | 17.3077 |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3