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

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: 1.2511
- Bleu: 14.6038
- Gen Len: 15.5513

## 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: 4
- total_train_batch_size: 64
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 1.3824        | 0.8   | 1500  | 1.3011          | 11.4445 | 15.774  |
| 1.0646        | 1.61  | 3000  | 1.1916          | 13.1811 | 15.6757 |
| 0.8071        | 2.41  | 4500  | 1.1864          | 14.1901 | 15.2832 |
| 0.6496        | 3.22  | 6000  | 1.1979          | 14.3496 | 15.5238 |
| 0.6365        | 4.02  | 7500  | 1.2511          | 14.6014 | 15.5634 |
| 0.4942        | 4.82  | 9000  | 1.2521          | 14.3411 | 15.4888 |
| 0.3632        | 5.63  | 10500 | 1.3326          | 14.204  | 15.4075 |
| 0.2601        | 6.43  | 12000 | 1.4028          | 14.1714 | 15.4783 |
| 0.1919        | 7.23  | 13500 | 1.4764          | 13.9406 | 15.4543 |


### Framework versions

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