---
library_name: transformers
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: 47.355
---

<!-- 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: 1.3736
- Rouge1: 47.355
- Rouge2: 23.7601
- Rougel: 39.8403
- Rougelsum: 43.4718
- Gen Len: 17.1575

## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.3641        | 1.0   | 921  | 1.3780          | 47.4054 | 23.6308 | 39.8273 | 43.3697   | 17.3004 |
| 1.3074        | 2.0   | 1842 | 1.3736          | 47.355  | 23.7601 | 39.8403 | 43.4718   | 17.1575 |
| 1.2592        | 3.0   | 2763 | 1.3740          | 47.2208 | 23.4972 | 39.7293 | 43.2546   | 17.2320 |
| 1.2232        | 4.0   | 3684 | 1.3794          | 47.9156 | 24.2451 | 40.2628 | 43.9122   | 17.4017 |
| 1.2042        | 5.0   | 4605 | 1.3780          | 47.8982 | 24.1707 | 40.2955 | 43.8939   | 17.3712 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.0
- Tokenizers 0.19.1