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t5-small-finetuned-cnn

Summarization
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PyTorch
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t5
text2text-generation
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t5-small-finetuned-cnn
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---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- cnn_dailymail
metrics:
- rouge
model-index:
- name: t5-small-finetuned-cnn
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: cnn_dailymail
      type: cnn_dailymail
      args: 3.0.0
    metrics:
    - name: Rouge1
      type: rouge
      value: 33.2082
---

<!-- 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. -->

# t5-small-finetuned-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: 1.8436
- Rouge1: 33.2082
- Rouge2: 16.798
- Rougel: 28.9573
- Rougelsum: 31.1044

## 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 2.3793        | 1.0   | 359  | 1.8885          | 33.0321 | 16.7798 | 28.9367 | 30.9509   |
| 2.1432        | 2.0   | 718  | 1.8481          | 33.1559 | 16.8557 | 29.015  | 31.1122   |
| 2.0571        | 3.0   | 1077 | 1.8391          | 32.99   | 16.716  | 28.8118 | 30.9178   |
| 2.0001        | 4.0   | 1436 | 1.8357          | 33.0543 | 16.6731 | 28.8375 | 30.9604   |
| 1.9609        | 5.0   | 1795 | 1.8437          | 33.1019 | 16.7576 | 28.8669 | 31.001    |
| 1.925         | 6.0   | 2154 | 1.8402          | 33.1388 | 16.7539 | 28.8887 | 31.0262   |
| 1.9036        | 7.0   | 2513 | 1.8423          | 33.1825 | 16.759  | 28.9154 | 31.0656   |
| 1.8821        | 8.0   | 2872 | 1.8436          | 33.2082 | 16.798  | 28.9573 | 31.1044   |


### Framework versions

- Transformers 4.14.0
- Pytorch 1.5.0
- Datasets 2.3.2
- Tokenizers 0.10.3