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---
language:
- ko
- ja
base_model: facebook/mbart-large-50-many-to-many-mmt
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: tst-translation-output
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. -->
# tst-translation-output
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: 0.8968
- Bleu: 9.457
- Gen Len: 17.4895
## 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: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1500
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Bleu | Gen Len | Validation Loss |
|:-------------:|:-----:|:-----:|:-------:|:-------:|:---------------:|
| 1.1751 | 0.47 | 3000 | 7.6766 | 17.4644 | 1.1289 |
| 1.0268 | 0.93 | 6000 | 9.2277 | 17.7668 | 0.9895 |
| 0.8075 | 1.4 | 9000 | 9.1197 | 17.6811 | 0.9457 |
| 0.8082 | 1.87 | 12000 | 8.4837 | 17.4826 | 0.9053 |
| 0.5841 | 2.33 | 15000 | 9.8887 | 17.5166 | 0.9303 |
| 0.6142 | 2.8 | 18000 | 9.547 | 17.426 | 0.9142 |
| 0.4119 | 3.26 | 21000 | 9.5055 | 17.3378 | 0.9879 |
| 0.2837 | 7.46 | 24000 | 11.0549 | 17.2982 | 1.0063 |
| 0.1792 | 8.4 | 27000 | 8.9031 | 17.2801 | 1.0856 |
| 0.1204 | 9.33 | 30000 | 1.1643 | 11.3498 | 17.2986 |
| 0.0826 | 10.26 | 33000 | 1.2319 | 10.796 | 17.3627 |
| 0.0617 | 11.19 | 36000 | 1.2785 | 10.6211 | 17.3748 |
| 0.0523 | 12.13 | 39000 | 1.3217 | 9.8848 | 17.3358 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
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