---
language:
- flan_t5_test_2023_01_31
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: flan-t5-base-samsum
  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: 47.4339
---

<!-- 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-samsum

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: 1.3772
- Rouge1: 47.4339
- Rouge2: 23.9608
- Rougel: 40.0566
- Rougelsum: 43.6981
- Gen Len: 17.3162

## 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 | 1.3829          | 46.5338 | 23.1342 | 39.4468 | 42.8518   | 17.0977 |
| 1.3534        | 2.0   | 3684 | 1.3732          | 47.0913 | 23.5016 | 39.5941 | 43.238    | 17.4554 |
| 1.2795        | 3.0   | 5526 | 1.3709          | 46.8916 | 23.3226 | 39.5661 | 43.1582   | 17.2027 |
| 1.2313        | 4.0   | 7368 | 1.3736          | 47.441  | 23.7501 | 40.0446 | 43.6336   | 17.2198 |
| 1.1934        | 5.0   | 9210 | 1.3772          | 47.4339 | 23.9608 | 40.0566 | 43.6981   | 17.3162 |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2