---
language:
- vie
- lao
license: apache-2.0
base_model: google/mt5-xl
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: mt5-full-v6.1
  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-full-v6.1

This model is a fine-tuned version of [google/mt5-xl](https://huggingface.co/google/mt5-xl) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8711
- Bleu: 19.5743
- Gen Len: 41.77

## 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-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 3435
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step   | Bleu   | Gen Len | Validation Loss |
|:-------------:|:-----:|:------:|:------:|:-------:|:---------------:|
| 1.5671        | 0.14  | 5000   | 6.5196 | 18.9699 | 1.1691          |
| 1.2277        | 0.28  | 10000  | 7.082  | 18.9724 | 1.0592          |
| 1.1316        | 0.42  | 15000  | 7.3283 | 18.9825 | 1.0112          |
| 1.0833        | 0.56  | 20000  | 7.4462 | 18.977  | 0.9728          |
| 1.0339        | 0.7   | 25000  | 8.0126 | 18.982  | 0.9546          |
| 1.025         | 0.83  | 30000  | 7.7648 | 18.9805 | 0.9337          |
| 0.9733        | 0.97  | 35000  | 7.9496 | 18.9815 | 0.9228          |
| 0.9035        | 1.11  | 40000  | 7.689  | 18.9795 | 0.9162          |
| 0.9386        | 1.25  | 45000  | 7.6781 | 18.9825 | 0.9039          |
| 0.9073        | 1.39  | 50000  | 7.8607 | 18.9805 | 0.8986          |
| 0.8928        | 1.53  | 55000  | 8.0666 | 18.981  | 0.8942          |
| 0.884         | 1.67  | 60000  | 8.1679 | 18.9785 | 0.8874          |
| 0.8786        | 1.81  | 65000  | 7.8516 | 18.9805 | 0.8831          |
| 0.8899        | 1.95  | 70000  | 0.8789 | 7.9392  | 18.9785         |
| 0.8638        | 2.09  | 75000  | 0.8781 | 8.1623  | 18.979          |
| 0.8293        | 2.22  | 80000  | 0.8752 | 8.0989  | 18.98           |
| 0.8625        | 2.36  | 85000  | 0.8743 | 8.176   | 18.979          |
| 0.8605        | 2.5   | 90000  | 0.8721 | 8.0117  | 18.9805         |
| 0.8479        | 2.64  | 95000  | 0.8711 | 8.1008  | 18.978          |
| 0.8391        | 2.78  | 100000 | 0.8708 | 8.2041  | 18.9795         |
| 0.8649        | 2.92  | 105000 | 0.8710 | 8.1488  | 18.9785         |


### Framework versions

- Transformers 4.37.1
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1