---
language:
- ko
- en
base_model: facebook/mbart-large-50-many-to-many-mmt
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: ko-en_mbartLarge_mid3
  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. -->

# ko-en_mbartLarge_mid3

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: 1.3246
- Bleu: 22.9623
- Gen Len: 18.7197

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 1000
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 1.5377        | 0.23  | 2000  | 1.6122          | 17.2009 | 18.7106 |
| 1.3891        | 0.46  | 4000  | 1.5059          | 19.3345 | 18.7688 |
| 1.2812        | 0.7   | 6000  | 1.4348          | 20.6032 | 18.9022 |
| 1.2374        | 0.93  | 8000  | 1.4035          | 21.2391 | 18.8434 |
| 1.1734        | 1.16  | 10000 | 1.4039          | 21.304  | 18.9964 |
| 1.1531        | 1.39  | 12000 | 1.3694          | 21.9087 | 18.8573 |
| 1.1158        | 1.62  | 14000 | 1.3574          | 22.004  | 18.5485 |
| 1.0941        | 1.86  | 16000 | 1.3457          | 21.9785 | 18.7119 |
| 0.9809        | 2.09  | 18000 | 1.3495          | 22.7983 | 18.8011 |
| 0.9834        | 2.32  | 20000 | 1.3429          | 22.5654 | 18.9416 |
| 0.9981        | 2.55  | 22000 | 1.3246          | 22.9493 | 18.7364 |
| 1.0074        | 2.78  | 24000 | 1.3539          | 22.3874 | 18.4428 |
| 0.9752        | 3.02  | 26000 | 1.3587          | 22.1907 | 18.8139 |
| 0.8858        | 3.25  | 28000 | 1.3457          | 22.82   | 18.8021 |
| 0.8895        | 3.48  | 30000 | 1.3603          | 22.1575 | 18.5638 |


### Framework versions

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