---
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_linear_decay
  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_linear_decay

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: 1.2291
- Bleu: 26.9332
- Gen Len: 18.743

## 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: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 1.4396        | 0.23  | 1000  | 1.3815          | 21.7052 | 18.6047 |
| 1.338         | 0.46  | 2000  | 1.3044          | 23.7087 | 18.9939 |
| 1.2938        | 0.7   | 3000  | 1.2556          | 24.6339 | 18.8866 |
| 1.251         | 0.93  | 4000  | 1.2229          | 25.2975 | 19.0918 |
| 0.9843        | 1.16  | 5000  | 1.2309          | 25.609  | 18.7589 |
| 0.9874        | 1.39  | 6000  | 1.2101          | 26.1792 | 18.8287 |
| 0.9838        | 1.62  | 7000  | 1.2053          | 26.024  | 18.4025 |
| 0.9927        | 1.86  | 8000  | 1.1907          | 26.3148 | 19.09   |
| 0.7835        | 2.09  | 9000  | 1.2300          | 26.5613 | 18.7196 |
| 0.7437        | 2.32  | 10000 | 1.2358          | 26.8232 | 18.6513 |
| 0.7585        | 2.55  | 11000 | 1.2291          | 26.9203 | 18.7513 |
| 0.7631        | 2.78  | 12000 | 1.2170          | 26.8668 | 18.5441 |
| 0.7428        | 3.02  | 13000 | 1.3272          | 26.2506 | 18.6959 |
| 0.5502        | 3.25  | 14000 | 1.3392          | 26.419  | 18.6722 |
| 0.5577        | 3.48  | 15000 | 1.3204          | 26.1621 | 18.7036 |


### Framework versions

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