---
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: 42.6378
---

<!-- 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: 1.6629
- Rouge1: 42.6378
- Rouge2: 18.2896
- Rougel: 35.1851
- Rougelsum: 38.8113
- Gen Len: 16.8596

## 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: 40
- eval_batch_size: 40
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.7932        | 0.27  | 100  | 1.6830          | 42.7032 | 18.4803 | 35.278  | 38.9331   | 17.0403 |
| 1.8102        | 0.54  | 200  | 1.6701          | 42.2811 | 18.2246 | 35.0893 | 38.4619   | 16.7265 |
| 1.8279        | 0.81  | 300  | 1.6658          | 42.6465 | 18.6939 | 35.4208 | 38.9399   | 16.8120 |
| 1.802         | 1.08  | 400  | 1.6633          | 42.5867 | 18.3579 | 35.3253 | 38.7049   | 16.6862 |
| 1.773         | 1.36  | 500  | 1.6629          | 42.6378 | 18.2896 | 35.1851 | 38.8113   | 16.8596 |
| 1.7752        | 1.63  | 600  | 1.6598          | 42.7111 | 18.3689 | 35.4218 | 38.8698   | 16.9328 |
| 1.7688        | 1.9   | 700  | 1.6589          | 42.6972 | 18.3536 | 35.3153 | 38.7976   | 17.0073 |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0