---
tags:
- generated_from_trainer
datasets:
- xsum
language:
- en
metrics:
- rouge
model-index:
- name: t5-small-finetuned-xsum-finetuned-xsum
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: xsum
      type: xsum
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 27.7165
---

<!-- 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-finetuned-xsum

This model is a fine-tuned version of [st3rl4nce/t5-small-finetuned-xsum](https://huggingface.co/st3rl4nce/t5-small-finetuned-xsum) on the xsum dataset.
It achieves the following results on the evaluation set:
- eval_loss: 2.5146
- eval_rouge1: 27.7165
- eval_rouge2: 7.3585
- eval_rougeL: 21.7684
- eval_rougeLsum: 21.7758
- eval_gen_len: 18.8131
- eval_runtime: 667.5713
- eval_samples_per_second: 16.975
- eval_steps_per_second: 1.062
- epoch: 0.01
- step: 113

## 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: 1
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3