---
language:
- ko
- en
base_model: facebook/mbart-large-50-many-to-many-mmt
tags:
- generated_from_trainer
metrics:
- bleu
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: 1.4429
- Bleu: 21.4825
- Gen Len: 18.792

## 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: 1000
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 1.3784        | 0.23  | 2000  | 1.5514          | 18.2602 | 19.2938 |
| 1.2953        | 0.46  | 4000  | 1.5006          | 19.6277 | 18.7905 |
| 1.2446        | 0.7   | 6000  | 1.4664          | 20.2667 | 19.2503 |
| 1.2095        | 0.93  | 8000  | 1.4482          | 20.8962 | 18.9352 |
| 0.9279        | 1.16  | 10000 | 1.4799          | 20.9876 | 19.093  |
| 0.9604        | 1.39  | 12000 | 1.4672          | 21.261  | 18.8735 |
| 0.9543        | 1.62  | 14000 | 1.4611          | 21.1987 | 18.8396 |
| 0.9532        | 1.86  | 16000 | 1.4429          | 21.4802 | 18.8239 |
| 0.6681        | 2.09  | 18000 | 1.5450          | 21.1981 | 18.6116 |
| 0.6971        | 2.32  | 20000 | 1.5516          | 21.3101 | 18.892  |
| 0.7283        | 2.55  | 22000 | 1.5405          | 20.902  | 18.6448 |
| 0.7308        | 2.78  | 24000 | 1.5363          | 21.3017 | 18.2578 |


### Framework versions

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