---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
model-index:
- name: ntu_adl_summarization_mt5_s
  results: []
datasets:
- xjlulu/ntu_adl_summarization
language:
- zh
metrics:
- rouge
pipeline_tag: summarization
---

<!-- 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. -->

# ntu_adl_summarization_mt5_s

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6583
- Rouge-1: 21.9729
- Rouge-2: 7.6735
- Rouge-l: 19.7497
- Ave Gen Len: 17.3098

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 | Rouge-1 | Rouge-2 | Rouge-l | Ave Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-----------:|
| 5.4447        | 1.0   | 1357  | 4.1235          | 17.7916 | 5.9785  | 16.5599 | 12.7161     |
| 4.7463        | 2.0   | 2714  | 3.9569          | 19.6608 | 6.7631  | 18.0768 | 14.8245     |
| 4.5203        | 3.0   | 4071  | 3.8545          | 20.5626 | 7.0737  | 18.7628 | 16.3307     |
| 4.4285        | 4.0   | 5428  | 3.7825          | 21.0690 | 7.2030  | 19.0863 | 16.7841     |
| 4.3196        | 5.0   | 6785  | 3.7269          | 21.2881 | 7.3307  | 19.2588 | 16.9276     |
| 4.2662        | 6.0   | 8142  | 3.7027          | 21.5793 | 7.5122  | 19.4806 | 17.0333     |
| 4.2057        | 7.0   | 9499  | 3.6764          | 21.7949 | 7.5987  | 19.6082 | 17.1811     |
| 4.1646        | 8.0   | 10856 | 3.6671          | 21.8164 | 7.5705  | 19.6207 | 17.2550     |
| 4.1399        | 9.0   | 12213 | 3.6602          | 21.9381 | 7.6577  | 19.7089 | 17.3014     |
| 4.1479        | 10.0  | 13570 | 3.6583          | 21.9729 | 7.6735  | 19.7497 | 17.3098     |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1