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
      args: 3.0.0
    metrics:
    - type: rouge
      value: 24.7231
      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: 1.8412
- Rouge1: 24.7231
- Rouge2: 12.292
- Rougel: 20.5347
- Rougelsum: 23.4668

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 2.0318        | 1.0   | 718  | 1.8028          | 24.5415 | 12.0907 | 20.5343 | 23.3386   |
| 1.8307        | 2.0   | 1436 | 1.8028          | 24.0965 | 11.6367 | 20.2078 | 22.8138   |
| 1.6881        | 3.0   | 2154 | 1.8136          | 25.0822 | 12.6509 | 20.9523 | 23.8303   |
| 1.5778        | 4.0   | 2872 | 1.8269          | 24.4271 | 11.8443 | 20.2281 | 23.0941   |
| 1.501         | 5.0   | 3590 | 1.8412          | 24.7231 | 12.292  | 20.5347 | 23.4668   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
