transformers pytorch mbart text2text-generation generated_from_trainer ko en base_model:facebook/mbart-large-50-many-to-many-mmt autotrain_compatible endpoints_compatible region:us
---
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_batch
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ko-en_mbartLarge_exp20p_batch

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: 1.2035
- Bleu: 27.8233
- Gen Len: 18.6226

## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 2000
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 1.0603        | 1.86  | 4000  | 1.1474          | 27.7215 | 18.8456 |
| 0.6774        | 3.71  | 8000  | 1.2035          | 27.8224 | 18.6267 |
| 0.4006        | 5.57  | 12000 | 1.4321          | 27.049  | 18.5618 |
| 0.2328        | 7.43  | 16000 | 1.7316          | 25.8623 | 18.4608 |
| 0.1369        | 9.28  | 20000 | 1.9367          | 25.6902 | 18.3337 |
| 0.1067        | 11.14 | 24000 | 2.0868          | 26.0105 | 18.4579 |


### Framework versions

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