---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-xlsum-en-zh
  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. -->

# mt5-small-finetuned-xlsum-en-zh

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2988
- Rouge1: 12.7272
- Rouge2: 2.4338
- Rougel: 10.5647
- Rougelsum: 10.5889

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 6.215         | 1.0   | 1000 | 3.5021          | 10.9361 | 1.9845 | 9.1348  | 9.0929    |
| 4.6051        | 2.0   | 2000 | 3.4190          | 11.6653 | 2.0884 | 9.6847  | 9.7251    |
| 4.3735        | 3.0   | 3000 | 3.3685          | 12.1941 | 2.2109 | 10.2818 | 10.237    |
| 4.2439        | 4.0   | 4000 | 3.3417          | 12.6308 | 2.4293 | 10.5036 | 10.5079   |
| 4.1552        | 5.0   | 5000 | 3.3148          | 12.5122 | 2.2873 | 10.3496 | 10.3545   |
| 4.0853        | 6.0   | 6000 | 3.3112          | 12.6426 | 2.3154 | 10.5514 | 10.5622   |
| 4.0508        | 7.0   | 7000 | 3.3048          | 12.843  | 2.3893 | 10.7232 | 10.7357   |
| 4.0293        | 8.0   | 8000 | 3.2988          | 12.7272 | 2.4338 | 10.5647 | 10.5889   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0