---
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_exp10p
  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_exp10p

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: 1.1283
- Bleu: 28.8237
- Gen Len: 18.5382

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 1.4782        | 0.31  | 2000  | 1.4360          | 21.538  | 18.6032 |
| 1.3618        | 0.62  | 4000  | 1.3226          | 23.8354 | 18.5594 |
| 1.2983        | 0.93  | 6000  | 1.2637          | 25.0795 | 18.7894 |
| 1.2065        | 1.24  | 8000  | 1.2371          | 25.7409 | 18.5615 |
| 1.1926        | 1.55  | 10000 | 1.2116          | 26.0527 | 18.4019 |
| 1.1734        | 1.86  | 12000 | 1.1907          | 26.9802 | 18.6141 |
| 1.0677        | 2.17  | 14000 | 1.1802          | 27.1925 | 18.4547 |
| 1.0773        | 2.48  | 16000 | 1.1655          | 27.5641 | 18.6726 |
| 1.0688        | 2.78  | 18000 | 1.1521          | 27.6261 | 18.6127 |
| 0.9542        | 3.09  | 20000 | 1.1709          | 27.16   | 18.3782 |
| 0.9531        | 3.4   | 22000 | 1.1435          | 28.0684 | 18.436  |
| 0.9756        | 3.71  | 24000 | 1.1565          | 27.6025 | 18.7284 |
| 0.9964        | 4.02  | 26000 | 1.2285          | 25.6999 | 18.3255 |
| 0.9721        | 4.33  | 28000 | 1.1881          | 27.3499 | 18.5409 |
| 0.9237        | 4.64  | 30000 | 1.1497          | 28.2692 | 18.6614 |
| 0.9041        | 4.95  | 32000 | 1.1283          | 28.8215 | 18.5493 |
| 0.6842        | 5.26  | 34000 | 1.1741          | 28.6873 | 18.515  |
| 0.7101        | 5.57  | 36000 | 1.1876          | 28.0778 | 18.3422 |
| 0.7697        | 5.88  | 38000 | 1.1898          | 27.6338 | 18.6766 |
| 0.6028        | 6.19  | 40000 | 1.2393          | 28.0713 | 18.5903 |


### Framework versions

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