---
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: flan-t5-small-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: 43.8171
---

<!-- 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-small-samsum

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6335
- Rouge1: 43.8171
- Rouge2: 19.6313
- Rougel: 36.3793
- Rougelsum: 39.8169
- Gen Len: 16.7924

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.8193        | 1.0   | 1842 | 1.6613          | 42.6528 | 18.8812 | 35.4634 | 38.9086   | 16.8669 |
| 1.7355        | 2.0   | 3684 | 1.6374          | 43.2587 | 18.9454 | 35.8785 | 39.2731   | 16.7937 |
| 1.6946        | 3.0   | 5526 | 1.6364          | 43.3101 | 18.9886 | 35.9659 | 39.2743   | 16.7973 |
| 1.6654        | 4.0   | 7368 | 1.6341          | 43.7224 | 19.3408 | 36.1299 | 39.703    | 16.8376 |
| 1.6372        | 5.0   | 9210 | 1.6335          | 43.8171 | 19.6313 | 36.3793 | 39.8169   | 16.7924 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0