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---
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_exp20p
  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_exp20p

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: 1.1451
- Bleu: 28.9507
- Gen Len: 18.6702

## 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: 2000
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 1.4008        | 0.46  | 4000  | 1.3739          | 22.7174 | 18.7094 |
| 1.2847        | 0.93  | 8000  | 1.2652          | 24.8557 | 18.7254 |
| 1.2009        | 1.39  | 12000 | 1.2082          | 26.2074 | 18.7513 |
| 1.1686        | 1.86  | 16000 | 1.1841          | 26.304  | 19.161  |
| 1.0205        | 2.32  | 20000 | 1.1441          | 27.8937 | 18.6638 |
| 1.0217        | 2.78  | 24000 | 1.1301          | 28.4149 | 18.6666 |
| 0.8876        | 3.25  | 28000 | 1.1270          | 28.5803 | 18.6229 |
| 0.9024        | 3.71  | 32000 | 1.1181          | 28.852  | 18.7813 |
| 0.7927        | 4.18  | 36000 | 1.1393          | 28.3975 | 18.4863 |
| 0.8174        | 4.64  | 40000 | 1.1249          | 28.6313 | 18.3916 |
| 0.7434        | 5.11  | 44000 | 1.1696          | 28.2898 | 18.7739 |
| 0.7416        | 5.57  | 48000 | 1.1451          | 28.9507 | 18.6744 |
| 0.689         | 6.03  | 52000 | 1.1759          | 28.3532 | 18.4481 |
| 0.7238        | 6.5   | 56000 | 1.1825          | 28.3827 | 18.7038 |
| 0.7238        | 6.96  | 60000 | 1.1676          | 28.8248 | 18.5073 |
| 0.657         | 7.43  | 64000 | 1.2514          | 27.4378 | 18.4196 |


### Framework versions

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