---
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-base_V25775
  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-base_V25775

This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1251
- Rouge1: 28.2174
- Rouge2: 10.5032
- Rougel: 19.8511
- Rougelsum: 23.3756
- Gen Len: 72.3391

## 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: 3
- eval_batch_size: 3
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 6.8396        | 0.81  | 500   | 2.5158          | 15.7446 | 6.4867  | 12.6043 | 13.8967   | 31.1588 |
| 3.1783        | 1.61  | 1000  | 2.3673          | 21.0031 | 8.2119  | 15.9097 | 17.9958   | 46.0086 |
| 3.0094        | 2.42  | 1500  | 2.3091          | 20.5903 | 8.1394  | 15.7354 | 17.696    | 44.7339 |
| 2.8754        | 3.23  | 2000  | 2.2652          | 22.3129 | 8.6681  | 16.4687 | 18.8755   | 48.9485 |
| 2.7643        | 4.03  | 2500  | 2.2320          | 22.6675 | 8.8846  | 16.7258 | 19.0948   | 48.6781 |
| 2.7           | 4.84  | 3000  | 2.2190          | 24.1409 | 9.4362  | 17.7197 | 20.2512   | 52.8498 |
| 2.6373        | 5.65  | 3500  | 2.2100          | 24.594  | 9.4296  | 18.0182 | 20.6398   | 55.0687 |
| 2.6182        | 6.45  | 4000  | 2.2016          | 25.0763 | 9.432   | 18.1113 | 20.6752   | 57.4549 |
| 2.5552        | 7.26  | 4500  | 2.1767          | 26.6143 | 10.1357 | 19.004  | 22.0372   | 62.6738 |
| 2.5319        | 8.06  | 5000  | 2.1665          | 27.0349 | 10.3809 | 19.3472 | 22.5876   | 64.7167 |
| 2.5145        | 8.87  | 5500  | 2.1705          | 26.6323 | 9.956   | 18.9994 | 22.119    | 62.3176 |
| 2.4923        | 9.68  | 6000  | 2.1499          | 27.0052 | 10.0351 | 19.2887 | 22.4559   | 64.2747 |
| 2.4367        | 10.48 | 6500  | 2.1418          | 27.0134 | 10.1253 | 19.2614 | 22.4648   | 65.2661 |
| 2.4312        | 11.29 | 7000  | 2.1503          | 27.1655 | 9.9501  | 19.1768 | 22.3967   | 66.6953 |
| 2.4186        | 12.1  | 7500  | 2.1370          | 26.6422 | 9.7971  | 19.0065 | 22.0444   | 65.9571 |
| 2.3977        | 12.9  | 8000  | 2.1395          | 27.5204 | 10.3095 | 19.4189 | 22.7497   | 69.0901 |
| 2.3596        | 13.71 | 8500  | 2.1302          | 27.685  | 10.1479 | 19.4521 | 22.7892   | 70.0644 |
| 2.3951        | 14.52 | 9000  | 2.1298          | 27.8389 | 10.2493 | 19.6671 | 22.933    | 70.7897 |
| 2.3433        | 15.32 | 9500  | 2.1238          | 27.9095 | 10.33   | 19.6428 | 22.9721   | 70.4206 |
| 2.3789        | 16.13 | 10000 | 2.1271          | 28.0755 | 10.5819 | 19.9535 | 23.2605   | 69.97   |
| 2.3331        | 16.94 | 10500 | 2.1240          | 28.1362 | 10.4656 | 19.8198 | 23.1857   | 70.9485 |
| 2.3395        | 17.74 | 11000 | 2.1245          | 28.1459 | 10.4803 | 19.801  | 23.2469   | 71.1288 |
| 2.3238        | 18.55 | 11500 | 2.1273          | 28.2156 | 10.4437 | 19.858  | 23.3457   | 73.485  |
| 2.3181        | 19.35 | 12000 | 2.1251          | 28.2174 | 10.5032 | 19.8511 | 23.3756   | 72.3391 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0
- Datasets 2.12.0
- Tokenizers 0.13.3