---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-base-finetuned-multi-news
  results: []
---

<!-- 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-base-finetuned-multi-news

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2612
- Rouge1: 16.6322
- Rouge2: 5.7556
- Rougel: 12.4728
- Rougelsum: 14.4814

## 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: 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: 8

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 2.5641        | 1.0   | 1250  | 2.2636          | 16.6762 | 5.7127 | 12.4648 | 14.5499   |
| 2.3542        | 2.0   | 2500  | 2.2439          | 16.7381 | 5.7345 | 12.5515 | 14.5785   |
| 2.2487        | 3.0   | 3750  | 2.2388          | 16.8879 | 5.8792 | 12.6417 | 14.8011   |
| 2.1705        | 4.0   | 5000  | 2.2413          | 16.5921 | 5.7804 | 12.4539 | 14.4865   |
| 2.1083        | 5.0   | 6250  | 2.2459          | 16.6878 | 5.8593 | 12.5132 | 14.5473   |
| 2.0622        | 6.0   | 7500  | 2.2495          | 16.7267 | 5.7825 | 12.48   | 14.5309   |
| 2.0297        | 7.0   | 8750  | 2.2581          | 16.633  | 5.748  | 12.4418 | 14.4796   |
| 2.0084        | 8.0   | 10000 | 2.2612          | 16.6322 | 5.7556 | 12.4728 | 14.4814   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3