---
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: 47.3683
---

<!-- 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: 1.3716
- Rouge1: 47.3683
- Rouge2: 24.0343
- Rougel: 39.9874
- Rougelsum: 43.6453
- Gen Len: 17.3004

## 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.4531        | 1.0   | 1842  | 1.3836          | 46.4391 | 23.0513 | 39.1448 | 42.8774   | 17.1868 |
| 1.3433        | 2.0   | 3684  | 1.3729          | 47.0465 | 23.4504 | 39.8361 | 43.3316   | 17.2613 |
| 1.2767        | 3.0   | 5526  | 1.3716          | 47.3683 | 24.0343 | 39.9874 | 43.6453   | 17.3004 |
| 1.2117        | 4.0   | 7368  | 1.3739          | 47.6321 | 24.1445 | 40.3378 | 43.9123   | 17.0989 |
| 1.1622        | 5.0   | 9210  | 1.3826          | 47.6786 | 23.9568 | 40.2743 | 43.7625   | 17.0879 |
| 1.1387        | 6.0   | 11052 | 1.3920          | 47.6434 | 24.0265 | 40.2093 | 43.9179   | 17.3712 |
| 1.1011        | 7.0   | 12894 | 1.3947          | 47.6658 | 24.0395 | 40.3477 | 43.8425   | 17.2186 |
| 1.0755        | 8.0   | 14736 | 1.4059          | 47.5613 | 24.0555 | 40.181  | 43.7645   | 17.1490 |
| 1.0514        | 9.0   | 16578 | 1.4053          | 47.9552 | 24.2395 | 40.3731 | 44.0694   | 17.3602 |
| 1.0311        | 10.0  | 18420 | 1.4114          | 48.0582 | 24.3022 | 40.4713 | 44.1136   | 17.3175 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3