---
library_name: transformers
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
model-index:
- name: mt5_base_EN_TH_sch_wiki
  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_EN_TH_sch_wiki

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: nan
- Rouge2 Precision: 0.0098
- Rouge2 Recall: 0.0051
- Rouge2 Fmeasure: 0.0065

## 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: 5e-05
- train_batch_size: 45
- eval_batch_size: 16
- seed: 42
- optimizer: Use 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.0           | 1.0   | 2879  | nan             | 0.0098           | 0.0051        | 0.0065          |
| 0.0           | 2.0   | 5758  | nan             | 0.0098           | 0.0051        | 0.0065          |
| 0.0           | 3.0   | 8637  | nan             | 0.0098           | 0.0051        | 0.0065          |
| 0.0           | 4.0   | 11516 | nan             | 0.0098           | 0.0051        | 0.0065          |
| 0.0           | 5.0   | 14395 | nan             | 0.0098           | 0.0051        | 0.0065          |
| 0.0           | 6.0   | 17274 | nan             | 0.0098           | 0.0051        | 0.0065          |
| 0.0           | 7.0   | 20153 | nan             | 0.0098           | 0.0051        | 0.0065          |
| 0.0           | 8.0   | 23032 | nan             | 0.0098           | 0.0051        | 0.0065          |
| 0.0           | 9.0   | 25911 | nan             | 0.0098           | 0.0051        | 0.0065          |
| 0.0           | 10.0  | 28790 | nan             | 0.0098           | 0.0051        | 0.0065          |
| 0.0           | 11.0  | 31669 | nan             | 0.0098           | 0.0051        | 0.0065          |
| 0.0           | 12.0  | 34548 | nan             | 0.0098           | 0.0051        | 0.0065          |
| 0.0           | 13.0  | 37427 | nan             | 0.0098           | 0.0051        | 0.0065          |
| 0.0           | 14.0  | 40306 | nan             | 0.0098           | 0.0051        | 0.0065          |
| 0.0           | 15.0  | 43185 | nan             | 0.0098           | 0.0051        | 0.0065          |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.2.2
- Datasets 2.16.1
- Tokenizers 0.20.3