---
language:
- ko
- ja
base_model: facebook/mbart-large-50-many-to-many-mmt
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: tst-translation-output2
  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-output2

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: 0.9049
- Bleu: 10.3643
- Gen Len: 17.4046

## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 35

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 1.2499        | 0.23  | 1500  | 1.1806          | 6.1112  | 18.0495 |
| 1.1007        | 0.46  | 3000  | 1.0686          | 7.4845  | 17.6068 |
| 1.0334        | 0.68  | 4500  | 1.0013          | 9.0076  | 17.6214 |
| 0.992         | 0.91  | 6000  | 0.9599          | 8.6786  | 17.868  |
| 0.7881        | 1.14  | 7500  | 0.9644          | 9.2343  | 17.2061 |
| 0.7675        | 1.37  | 9000  | 0.9427          | 10.0578 | 17.6006 |
| 0.7665        | 1.59  | 10500 | 0.9238          | 10.436  | 17.2095 |
| 0.7707        | 1.82  | 12000 | 0.9049          | 10.5971 | 17.2971 |
| 0.6119        | 2.05  | 13500 | 0.9392          | 10.8369 | 17.3201 |
| 0.5579        | 2.28  | 15000 | 0.9429          | 10.3486 | 17.3221 |
| 0.5633        | 2.5   | 16500 | 0.9310          | 10.6114 | 17.3679 |
| 0.5764        | 2.73  | 18000 | 0.9265          | 9.9612  | 17.1339 |


### Framework versions

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