---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- cnn_dailymail
metrics:
- rouge
model-index:
- name: cnn_dailymail_t5_small
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: cnn_dailymail
      type: cnn_dailymail
      config: default
      split: train
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.2321
---



# cnn_dailymail_t5_small

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: 1.7271
- Rouge1: 0.2321
- Rouge2: 0.0955
- Rougel: 0.1887
- Rougelsum: 0.1887
- Gen Len: 18.9998

## Model description

Text-To-Text Transfer Transformer (T5)
T5-Small is the checkpoint with 60 million parameters.


## Intended uses & limitations

This is an exercise for finetuning of pretrained t5 model.

## Training and evaluation data


## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- 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 | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.9158        | 1.0   | 10000 | 1.7333          | 0.2313 | 0.0948 | 0.1879 | 0.1879    | 18.9998 |
| 1.9316        | 2.0   | 20000 | 1.7271          | 0.2321 | 0.0955 | 0.1887 | 0.1887    | 18.9998 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3