---
language:
- ko
- en
base_model: facebook/mbart-large-50-many-to-many-mmt
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: koen_mbartLarge_64p_run1
  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. -->

# koen_mbartLarge_64p_run1

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: 1.0989
- Bleu: 33.8958
- Gen Len: 18.5033

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 1.5543        | 0.13  | 2500  | 1.5068          | 25.2368 | 18.5097 |
| 1.4399        | 0.26  | 5000  | 1.3972          | 27.0554 | 18.5539 |
| 1.3448        | 0.39  | 7500  | 1.3132          | 28.8579 | 18.6315 |
| 1.3205        | 0.52  | 10000 | 1.2873          | 29.5611 | 18.7781 |
| 1.2786        | 0.65  | 12500 | 1.2399          | 30.3042 | 18.5644 |
| 1.2561        | 0.78  | 15000 | 1.2173          | 30.5801 | 19.0186 |
| 1.2479        | 0.91  | 17500 | 1.2125          | 30.8896 | 18.7636 |
| 1.1891        | 1.04  | 20000 | 1.1776          | 31.9834 | 18.7002 |
| 1.1943        | 1.17  | 22500 | 1.1651          | 32.0205 | 18.7054 |
| 1.1375        | 1.3   | 25000 | 1.1492          | 32.3658 | 18.6287 |
| 1.1351        | 1.43  | 27500 | 1.1460          | 32.339  | 18.7655 |
| 1.0859        | 1.56  | 30000 | 1.1623          | 31.5418 | 19.016  |
| 1.0373        | 1.69  | 32500 | 1.1383          | 32.672  | 18.7224 |
| 1.0824        | 1.82  | 35000 | 1.1232          | 33.2231 | 18.6697 |
| 1.0242        | 1.95  | 37500 | 1.1313          | 32.813  | 18.2553 |
| 1.0649        | 2.08  | 40000 | 1.1182          | 33.2021 | 18.7216 |
| 1.054         | 2.21  | 42500 | 1.1329          | 33.0588 | 18.4992 |
| 1.0143        | 2.34  | 45000 | 1.1187          | 33.2176 | 18.7156 |
| 1.0037        | 2.47  | 47500 | 1.1162          | 33.3754 | 18.6443 |
| 0.9928        | 2.61  | 50000 | 1.1306          | 33.0727 | 18.6361 |
| 0.9497        | 2.74  | 52500 | 1.1170          | 33.227  | 18.7638 |
| 1.0157        | 2.87  | 55000 | 1.1072          | 33.685  | 18.5847 |
| 0.9876        | 3.0   | 57500 | 1.1035          | 33.6971 | 18.6873 |
| 0.9665        | 3.13  | 60000 | 1.0989          | 33.8919 | 18.5258 |
| 0.9197        | 3.26  | 62500 | 1.1060          | 33.7036 | 18.5407 |
| 0.9427        | 3.39  | 65000 | 1.0995          | 33.7642 | 18.7    |
| 0.8993        | 3.52  | 67500 | 1.1364          | 33.1757 | 18.646  |
| 0.8957        | 3.65  | 70000 | 1.1251          | 33.0954 | 18.3129 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1