---
language:
- ja
- ko
base_model: facebook/mbart-large-50-many-to-many-mmt
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: jako_mbartLarge_6p
  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. -->

# jako_mbartLarge_6p

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: 1.1470
- Bleu: 21.2511
- Gen Len: 19.566

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 1.4498        | 0.48  | 1000 | 1.3303          | 16.7947 | 20.0778 |
| 1.263         | 0.96  | 2000 | 1.1884          | 18.6214 | 20.6673 |
| 0.8999        | 1.44  | 3000 | 1.1702          | 18.9014 | 19.4064 |
| 0.827         | 1.92  | 4000 | 1.1470          | 21.2511 | 19.566  |
| 0.5948        | 2.4   | 5000 | 1.2115          | 20.5498 | 19.3941 |
| 0.5404        | 2.88  | 6000 | 1.2167          | 21.2187 | 19.4357 |
| 0.3842        | 3.36  | 7000 | 1.2711          | 20.7732 | 19.3493 |
| 0.3419        | 3.84  | 8000 | 1.2910          | 20.7001 | 19.3106 |


### Framework versions

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