---
language:
- en
- ko
base_model: facebook/mbart-large-50-many-to-many-mmt
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: mbartLarge_mid_en-ko1
  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. -->

# mbartLarge_mid_en-ko1

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: 1.4106
- Bleu: 13.2758
- Gen Len: 16.235

## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 1.5855        | 1.12  | 1500  | 1.5215          | 11.5186 | 16.204  |
| 1.4287        | 2.24  | 3000  | 1.4549          | 12.2855 | 16.1497 |
| 1.2937        | 3.37  | 4500  | 1.4250          | 12.6484 | 16.2152 |
| 1.2444        | 4.49  | 6000  | 1.4165          | 13.0063 | 16.0749 |
| 1.1335        | 5.61  | 7500  | 1.4106          | 13.2758 | 16.235  |
| 1.0508        | 6.73  | 9000  | 1.4243          | 13.0601 | 15.86   |
| 0.9462        | 7.86  | 10500 | 1.4497          | 13.0828 | 16.0475 |
| 0.8464        | 8.98  | 12000 | 1.4692          | 13.5878 | 15.9308 |
| 0.6995        | 10.1  | 13500 | 1.5572          | 13.1085 | 15.9906 |


### Framework versions

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