---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: summarization
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: xsum
      type: xsum
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 23.9405
  - task:
      name: Summarization
      type: summarization
    dataset:
      type: xsum
      name: xsum
      config: default
      split: test
    metrics:
    - name: ROUGE-1
      type: rouge
      value: 18.0961
      verified: true
    - name: ROUGE-2
      type: rouge
      value: 3.3941
      verified: true
    - name: ROUGE-L
      type: rouge
      value: 14.3571
      verified: true
    - name: ROUGE-LSUM
      type: rouge
      value: 14.4809
      verified: true
---

<!-- 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. -->

# summarization

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6690
- Rouge1: 23.9405
- Rouge2: 5.0879
- Rougel: 18.4981
- Rougelsum: 18.5032
- Gen Len: 18.7376

## 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: 2e-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
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 2.9249        | 0.08  | 1000 | 2.6690          | 23.9405 | 5.0879 | 18.4981 | 18.5032   | 18.7376 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1