---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-cnndailymail-en
  results: []
datasets:
- cnn_dailymail
library_name: transformers
---

<!-- 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. -->

# mt5-small-finetuned-cnndailymail-en

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9001
- Rouge1: 0.2945
- Rouge2: 0.1496
- Rougel: 0.2717
- Rougelsum: 0.2755

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 3.108         | 1.0   | 6250  | 2.1633          | 0.2817 | 0.1398 | 0.2595 | 0.2633    |
| 2.3974        | 2.0   | 12500 | 2.0337          | 0.2894 | 0.1451 | 0.2671 | 0.2709    |
| 2.2688        | 3.0   | 18750 | 1.9802          | 0.2906 | 0.1454 | 0.2682 | 0.2720    |
| 2.1937        | 4.0   | 25000 | 1.9602          | 0.2899 | 0.1451 | 0.2674 | 0.2711    |
| 2.1403        | 5.0   | 31250 | 1.9341          | 0.2882 | 0.1442 | 0.2663 | 0.2702    |
| 2.1005        | 6.0   | 37500 | 1.9161          | 0.2931 | 0.1477 | 0.2705 | 0.2743    |
| 2.071         | 7.0   | 43750 | 1.9145          | 0.2929 | 0.1487 | 0.2706 | 0.2745    |
| 2.0476        | 8.0   | 50000 | 1.9088          | 0.2940 | 0.1495 | 0.2715 | 0.2752    |
| 2.0323        | 9.0   | 56250 | 1.9074          | 0.2943 | 0.1497 | 0.2717 | 0.2755    |
| 2.0203        | 10.0  | 62500 | 1.9001          | 0.2945 | 0.1496 | 0.2717 | 0.2755    |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2