transformers pytorch mbart text2text-generation generated_from_trainer ko ja base_model:facebook/mbart-large-50-many-to-many-mmt base_model:finetune:facebook/mbart-large-50-many-to-many-mmt autotrain_compatible endpoints_compatible region:us
---
base_model: facebook/mbart-large-50-many-to-many-mmt
language:
- ko
- ja
metrics:
- bleu
tags:
- generated_from_trainer
model-index:
- name: tst-translation-output
  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. -->

# tst-translation-output

This model is a fine-tuned version of [facebook/mbart-large-50-many-to-many-mmt](https://huggingface.co/facebook/mbart-large-50-many-to-many-mmt) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8968
- Bleu: 9.457
- Gen Len: 17.4895

## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1500
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step  | Bleu    | Gen Len | Validation Loss |
|:-------------:|:-----:|:-----:|:-------:|:-------:|:---------------:|
| 1.1751        | 0.47  | 3000  | 7.6766  | 17.4644 | 1.1289          |
| 1.0268        | 0.93  | 6000  | 9.2277  | 17.7668 | 0.9895          |
| 0.8075        | 1.4   | 9000  | 9.1197  | 17.6811 | 0.9457          |
| 0.8082        | 1.87  | 12000 | 8.4837  | 17.4826 | 0.9053          |
| 0.5841        | 2.33  | 15000 | 9.8887  | 17.5166 | 0.9303          |
| 0.6142        | 2.8   | 18000 | 9.547   | 17.426  | 0.9142          |
| 0.4119        | 3.26  | 21000 | 9.5055  | 17.3378 | 0.9879          |
| 0.2837        | 7.46  | 24000 | 11.0549 | 17.2982 | 1.0063          |
| 0.1792        | 8.4   | 27000 | 8.9031  | 17.2801 | 1.0856          |
| 0.1204        | 9.33  | 30000 | 1.1643  | 11.3498 | 17.2986         |
| 0.0826        | 10.26 | 33000 | 1.2319  | 10.796  | 17.3627         |
| 0.0617        | 11.19 | 36000 | 1.2785  | 10.6211 | 17.3748         |
| 0.0523        | 12.13 | 39000 | 1.3217  | 9.8848  | 17.3358         |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
