---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- cnn_dailymail
metrics:
- rouge
model-index:
- name: cnn_dailymail-summarization-t5-small-2022-09-08
  results:
  - task:
      name: Summarization
      type: summarization
    dataset:
      name: cnn_dailymail 3.0.0
      type: cnn_dailymail
      args: 3.0.0
    metrics:
    - name: Rouge1
      type: rouge
      value: 41.4235
---

<!-- 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. -->

# cnn_dailymail-summarization-t5-small-2022-09-08

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the cnn_dailymail 3.0.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6455
- Rouge1: 41.4235
- Rouge2: 19.0263
- Rougel: 29.2892
- Rougelsum: 38.6338
- Gen Len: 73.7273

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.8435        | 0.28  | 10000  | 1.6998          | 24.3321 | 11.599  | 20.1028 | 22.9562   | 18.9997 |
| 1.8464        | 0.56  | 20000  | 1.6814          | 24.4483 | 11.6789 | 20.1798 | 23.0508   | 18.9996 |
| 1.8332        | 0.84  | 30000  | 1.6738          | 24.5531 | 11.7949 | 20.2834 | 23.1588   | 18.9994 |
| 1.8054        | 1.11  | 40000  | 1.6636          | 24.6194 | 11.843  | 20.3375 | 23.2259   | 18.9991 |
| 1.7958        | 1.39  | 50000  | 1.6597          | 24.5017 | 11.7755 | 20.2439 | 23.1148   | 18.9998 |
| 1.8095        | 1.67  | 60000  | 1.6546          | 24.5126 | 11.8043 | 20.2603 | 23.1175   | 18.9999 |
| 1.8127        | 1.95  | 70000  | 1.6521          | 24.4845 | 11.8136 | 20.2557 | 23.1089   | 18.9999 |
| 1.7952        | 2.23  | 80000  | 1.6488          | 24.6217 | 11.8877 | 20.3555 | 23.2514   | 18.9996 |
| 1.7863        | 2.51  | 90000  | 1.6477          | 24.5616 | 11.8489 | 20.3021 | 23.1754   | 18.9996 |
| 1.7824        | 2.79  | 100000 | 1.6464          | 24.5852 | 11.8531 | 20.3172 | 23.2089   | 18.9998 |


### Framework versions

- Transformers 4.22.0.dev0
- Pytorch 1.12.1+cu102
- Datasets 2.4.0
- Tokenizers 0.12.1