transformers pytorch tensorboard t5 text2text-generation summarization generated_from_trainer dataset:cnn_dailymail license:apache-2.0 model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
datasets:
- cnn_dailymail
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: t5-small-finetuned-cnn-news
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: cnn_dailymail
      type: cnn_dailymail
      config: 3.0.0
      split: validation
      args: 3.0.0
    metrics:
    - type: rouge
      value: 23.5402
      name: Rouge1
---

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# t5-small-finetuned-cnn-news

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: 2.7209
- Rouge1: 23.5402
- Rouge2: 10.8834
- Rougel: 19.3936
- Rougelsum: 22.1513

## 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: 0.00056
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 2.2531        | 1.0   | 718  | 2.6722          | 23.3437 | 10.5433 | 19.2183 | 21.8989   |
| 2.1518        | 2.0   | 1436 | 2.7024          | 23.4068 | 10.716  | 19.0751 | 21.9328   |
| 2.0925        | 3.0   | 2154 | 2.7235          | 23.232  | 10.5236 | 19.2254 | 21.8598   |
| 2.0808        | 4.0   | 2872 | 2.7309          | 23.7401 | 10.7664 | 19.4651 | 22.2479   |
| 2.1114        | 5.0   | 3590 | 2.7209          | 23.5402 | 10.8834 | 19.3936 | 22.1513   |


### Framework versions

- Transformers 4.27.2
- Pytorch 1.13.1+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3
