---
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: 47.2327
---

<!-- 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: 1.3715
- Rouge1: 47.2327
- Rouge2: 23.7085
- Rougel: 39.6926
- Rougelsum: 43.4089
- Gen Len: 17.1868

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.4596        | 1.0   | 614  | 1.3916          | 46.7408 | 22.8901 | 38.9867 | 42.8599   | 17.3639 |
| 1.3941        | 2.0   | 1228 | 1.3760          | 47.1927 | 23.5198 | 39.7919 | 43.4399   | 17.3065 |
| 1.3488        | 3.0   | 1842 | 1.3715          | 47.2327 | 23.7085 | 39.6926 | 43.4089   | 17.1868 |
| 1.3244        | 4.0   | 2456 | 1.3742          | 47.1866 | 23.2968 | 39.5822 | 43.3795   | 17.3346 |
| 1.2788        | 5.0   | 3070 | 1.3766          | 46.9935 | 23.3295 | 39.5672 | 43.3056   | 17.2503 |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.0+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3