transformers pytorch tensorboard t5 text2text-generation generated_from_trainer summarization dataset:xsum dataset:autoevaluate/xsum-sample license:apache-2.0 model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
datasets:
- xsum
- autoevaluate/xsum-sample
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
- summarization
model-index:
- name: summarization
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: xsum
      type: xsum
      args: default
    metrics:
    - type: rouge
      value: 23.9405
      name: Rouge1
---

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# 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
