---
license: apache-2.0
base_model: google/flan-t5-base
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: 47.1046
---

<!-- 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: 1.3859
- Rouge1: 47.1046
- Rouge2: 23.264
- Rougel: 39.2757
- Rougelsum: 43.2598
- Gen Len: 17.3333

## 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: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.5121        | 0.08  | 50   | 1.4287          | 46.7868 | 22.863  | 38.971  | 42.8209   | 16.9634 |
| 1.46          | 0.16  | 100  | 1.4199          | 46.8031 | 22.8195 | 39.0708 | 42.8717   | 17.2393 |
| 1.4515        | 0.24  | 150  | 1.4147          | 46.6849 | 23.0376 | 38.9434 | 42.8344   | 17.1245 |
| 1.4679        | 0.33  | 200  | 1.4121          | 46.8756 | 22.8504 | 39.1671 | 43.1892   | 17.3431 |
| 1.451         | 0.41  | 250  | 1.4109          | 46.8572 | 23.09   | 39.2939 | 43.2955   | 17.2686 |
| 1.4434        | 0.49  | 300  | 1.4040          | 46.6829 | 23.071  | 39.3131 | 43.1432   | 16.9158 |
| 1.4417        | 0.57  | 350  | 1.4007          | 46.8637 | 23.0661 | 39.2462 | 43.1897   | 17.1172 |
| 1.4781        | 0.65  | 400  | 1.3952          | 46.8511 | 23.1134 | 39.3071 | 43.2164   | 17.2076 |
| 1.4626        | 0.73  | 450  | 1.3940          | 47.1533 | 23.2771 | 39.3094 | 43.2806   | 17.2222 |
| 1.4307        | 0.81  | 500  | 1.3955          | 46.9527 | 23.2227 | 39.2844 | 43.1903   | 17.2002 |
| 1.4586        | 0.9   | 550  | 1.3933          | 46.7523 | 23.1759 | 39.2675 | 43.1588   | 17.3040 |
| 1.4465        | 0.98  | 600  | 1.3905          | 46.855  | 23.3518 | 39.2879 | 43.2145   | 17.3468 |
| 1.381         | 1.06  | 650  | 1.3953          | 46.9719 | 22.9788 | 39.0886 | 43.1892   | 17.4066 |
| 1.4125        | 1.14  | 700  | 1.3922          | 46.535  | 23.0956 | 38.9275 | 42.9811   | 17.2381 |
| 1.3667        | 1.22  | 750  | 1.3922          | 47.3311 | 23.4123 | 39.5412 | 43.5624   | 17.2930 |
| 1.3878        | 1.3   | 800  | 1.3953          | 46.6737 | 23.2153 | 39.2982 | 43.2596   | 17.3358 |
| 1.3884        | 1.38  | 850  | 1.3931          | 46.9764 | 23.1561 | 39.1606 | 43.2115   | 17.3614 |
| 1.3766        | 1.47  | 900  | 1.3898          | 47.0466 | 23.1674 | 39.2822 | 43.293    | 17.3333 |
| 1.3727        | 1.55  | 950  | 1.3889          | 46.7311 | 23.0837 | 39.0882 | 43.0072   | 17.3211 |
| 1.4001        | 1.63  | 1000 | 1.3859          | 47.1046 | 23.264  | 39.2757 | 43.2598   | 17.3333 |
| 1.3894        | 1.71  | 1050 | 1.3874          | 47.2479 | 23.3762 | 39.4723 | 43.5241   | 17.3297 |
| 1.3697        | 1.79  | 1100 | 1.3860          | 47.1037 | 23.3894 | 39.3848 | 43.3875   | 17.3504 |
| 1.3886        | 1.87  | 1150 | 1.3862          | 47.0714 | 23.3937 | 39.4181 | 43.3841   | 17.3260 |
| 1.4037        | 1.95  | 1200 | 1.3861          | 47.0725 | 23.4085 | 39.3575 | 43.3676   | 17.3321 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.0+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3