---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
base_model: t5-small
pipeline_tag: summarization
model-index:
- name: t5-small-finetuned-xsum
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: xsum
      type: xsum
      config: default
      split: train[:10%]
      args: default
    metrics:
    - type: rouge
      value: 27.0616
      name: Rouge1
---

<!-- 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. -->

# t5-small-finetuned-xsum

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: 2.5622
- Rouge1: 27.0616
- Rouge2: 6.8574
- Rougel: 21.1087
- Rougelsum: 21.1175
- Gen Len: 18.8246

## 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
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 2.8879        | 1.0   | 1148 | 2.6353          | 25.4786 | 5.8199 | 19.7404 | 19.7497   | 18.8089 |
| 2.8178        | 2.0   | 2296 | 2.5951          | 26.2963 | 6.4255 | 20.5395 | 20.5304   | 18.8084 |
| 2.7831        | 3.0   | 3444 | 2.5741          | 26.7181 | 6.7174 | 20.8888 | 20.8914   | 18.806  |
| 2.7572        | 4.0   | 4592 | 2.5647          | 27.0071 | 6.8335 | 21.108  | 21.1149   | 18.8202 |
| 2.7476        | 5.0   | 5740 | 2.5622          | 27.0616 | 6.8574 | 21.1087 | 21.1175   | 18.8246 |


### Framework versions

- Transformers 4.40.1
- Pytorch 1.13.1+cu117
- Datasets 2.19.0
- Tokenizers 0.19.1