---
language:
- ko
- en
base_model: ./reduced_model
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: mbart_cycle0_ko-en
  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. -->

# mbart_cycle0_ko-en

This model is a fine-tuned version of reduced mbart-large-cc25(https://huggingface.co/facebook/mbart-large-cc25) on an custom dataset.
It achieves the following results on the evaluation set:
- Loss: 8.0362
- Bleu: 3.9193
- Gen Len: 19.5758

## 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
- total_train_batch_size: 16
- 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: 300
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| 8.5105        | 10.0  | 500  | 5.7366          | 1.0483 | 32.2222 |
| 1.3079        | 20.0  | 1000 | 7.1497          | 3.8281 | 17.3838 |
| 0.179         | 30.0  | 1500 | 7.7171          | 4.1437 | 18.6869 |
| 0.0535        | 40.0  | 2000 | 7.9881          | 4.1251 | 18.5455 |
| 0.0203        | 50.0  | 2500 | 8.0362          | 3.9193 | 19.5758 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3