---
library_name: transformers
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-synthetic-data-plus-translated-bs32ep20lr5e3
  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-synthetic-data-plus-translated-bs32ep20lr5e3

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: 1.3381
- Rouge1: 0.7165
- Rouge2: 0.6111
- Rougel: 0.7004
- Rougelsum: 0.7016

## 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: 0.0056
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 0.2243        | 1.0   | 38   | 0.9621          | 0.6801 | 0.5630 | 0.6599 | 0.6606    |
| 0.2209        | 2.0   | 76   | 0.9423          | 0.6766 | 0.5707 | 0.6633 | 0.6644    |
| 0.1953        | 3.0   | 114  | 0.9503          | 0.6525 | 0.5271 | 0.6361 | 0.6369    |
| 0.1812        | 4.0   | 152  | 0.9818          | 0.6811 | 0.5742 | 0.6672 | 0.6680    |
| 0.1418        | 5.0   | 190  | 0.9591          | 0.6868 | 0.5781 | 0.6700 | 0.6708    |
| 0.1312        | 6.0   | 228  | 1.0121          | 0.6900 | 0.5842 | 0.6734 | 0.6742    |
| 0.1236        | 7.0   | 266  | 0.9913          | 0.6787 | 0.5689 | 0.6652 | 0.6653    |
| 0.1068        | 8.0   | 304  | 0.9773          | 0.6886 | 0.5781 | 0.6749 | 0.6764    |
| 0.106         | 9.0   | 342  | 1.0201          | 0.6947 | 0.5825 | 0.6798 | 0.6802    |
| 0.084         | 10.0  | 380  | 1.0865          | 0.6861 | 0.5775 | 0.6726 | 0.6738    |
| 0.0744        | 11.0  | 418  | 1.0310          | 0.6997 | 0.5865 | 0.6849 | 0.6861    |
| 0.0618        | 12.0  | 456  | 1.1647          | 0.7118 | 0.6182 | 0.7016 | 0.7020    |
| 0.0493        | 13.0  | 494  | 1.1808          | 0.7089 | 0.6098 | 0.6959 | 0.6970    |
| 0.0472        | 14.0  | 532  | 1.2040          | 0.7087 | 0.6090 | 0.6956 | 0.6965    |
| 0.0399        | 15.0  | 570  | 1.1293          | 0.7065 | 0.6035 | 0.6953 | 0.6965    |
| 0.0346        | 16.0  | 608  | 1.2286          | 0.7078 | 0.6028 | 0.6928 | 0.6940    |
| 0.0255        | 17.0  | 646  | 1.2970          | 0.7114 | 0.6069 | 0.6986 | 0.7001    |
| 0.0241        | 18.0  | 684  | 1.3016          | 0.7053 | 0.5983 | 0.6893 | 0.6904    |
| 0.0217        | 19.0  | 722  | 1.3315          | 0.7137 | 0.6084 | 0.6999 | 0.7008    |
| 0.0196        | 20.0  | 760  | 1.3381          | 0.7165 | 0.6111 | 0.7004 | 0.7016    |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0