---
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: 43.9866
---

<!-- 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: 1.6311
- Rouge1: 43.9866
- Rouge2: 19.8759
- Rougel: 36.4981
- Rougelsum: 40.0333
- Gen Len: 16.9072

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.5782        | 1.0   | 1842 | 1.6428          | 43.7392 | 19.2055 | 36.2978 | 39.9317   | 16.8095 |
| 1.5494        | 2.0   | 3684 | 1.6316          | 44.0128 | 19.4478 | 36.4456 | 40.0738   | 16.9365 |
| 1.5445        | 3.0   | 5526 | 1.6356          | 44.0056 | 19.5202 | 36.3341 | 39.9956   | 16.9438 |
| 1.5379        | 4.0   | 7368 | 1.6339          | 43.8323 | 19.6412 | 36.2335 | 39.9361   | 16.9646 |
| 1.5392        | 5.0   | 9210 | 1.6311          | 43.9866 | 19.8759 | 36.4981 | 40.0333   | 16.9072 |


### Framework versions

- Transformers 4.34.1
- Pytorch 1.12.1+cu113
- Datasets 2.14.6
- Tokenizers 0.14.1