README.md

---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- cnn_dailymail
metrics:
- rouge
model-index:
- name: t5-small-finetuned-summarization-cnn
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: cnn_dailymail
      type: cnn_dailymail
      config: 3.0.0
      split: train[:2%]
      args: 3.0.0
    metrics:
    - name: Rouge1
      type: rouge
      value: 24.4825
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# t5-small-finetuned-summarization-cnn

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0105
- Rouge1: 24.4825
- Rouge2: 9.1573
- Rougel: 19.7135
- Rougelsum: 22.2551

## 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: 5.6e-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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 2.0389        | 1.0   | 718  | 2.0150          | 24.4413 | 9.1782 | 19.7202 | 22.2225   |
| 1.9497        | 2.0   | 1436 | 2.0105          | 24.4825 | 9.1573 | 19.7135 | 22.2551   |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.0
- Tokenizers 0.13.2