---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- xlsum
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-tradition-zh
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: xlsum
      type: xlsum
      args: chinese_traditional
    metrics:
    - name: Rouge1
      type: rouge
      value: 5.7806
---

<!-- 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-tradition-zh

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the xlsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9218
- Rouge1: 5.7806
- Rouge2: 1.266
- Rougel: 5.761
- Rougelsum: 5.7833

## 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: 6

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 4.542         | 1.0   | 2336  | 3.1979          | 4.8334 | 1.025  | 4.8142 | 4.8326    |
| 3.7542        | 2.0   | 4672  | 3.0662          | 5.2155 | 1.0978 | 5.2025 | 5.2158    |
| 3.5706        | 3.0   | 7008  | 3.0070          | 5.5471 | 1.3397 | 5.5386 | 5.5391    |
| 3.4668        | 4.0   | 9344  | 2.9537          | 5.5865 | 1.1558 | 5.5816 | 5.5964    |
| 3.4082        | 5.0   | 11680 | 2.9391          | 5.8061 | 1.3462 | 5.7944 | 5.812     |
| 3.375         | 6.0   | 14016 | 2.9218          | 5.7806 | 1.266  | 5.761  | 5.7833    |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1