---
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: 47.0613
---

<!-- 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: 1.3733
- Rouge1: 47.0613
- Rouge2: 23.3862
- Rougel: 39.7982
- Rougelsum: 43.3754
- Gen Len: 17.2308

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 461  | 1.3902          | 46.6525 | 23.0352 | 39.1875 | 42.9396   | 17.2601 |
| 1.4553        | 2.0   | 922  | 1.3787          | 47.2118 | 23.4378 | 39.5672 | 43.4137   | 17.1355 |
| 1.3763        | 3.0   | 1383 | 1.3737          | 47.2951 | 23.5914 | 39.7571 | 43.457    | 17.1966 |
| 1.3412        | 4.0   | 1844 | 1.3750          | 47.2382 | 23.697  | 39.9147 | 43.5955   | 17.3443 |
| 1.3045        | 5.0   | 2305 | 1.3733          | 47.0613 | 23.3862 | 39.7982 | 43.3754   | 17.2308 |


### Framework versions

- Transformers 4.42.4
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1