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---
language:
- ko
- en
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: 1.4429
- Bleu: 21.4825
- Gen Len: 18.792
## 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: 1000
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 1.3784 | 0.23 | 2000 | 1.5514 | 18.2602 | 19.2938 |
| 1.2953 | 0.46 | 4000 | 1.5006 | 19.6277 | 18.7905 |
| 1.2446 | 0.7 | 6000 | 1.4664 | 20.2667 | 19.2503 |
| 1.2095 | 0.93 | 8000 | 1.4482 | 20.8962 | 18.9352 |
| 0.9279 | 1.16 | 10000 | 1.4799 | 20.9876 | 19.093 |
| 0.9604 | 1.39 | 12000 | 1.4672 | 21.261 | 18.8735 |
| 0.9543 | 1.62 | 14000 | 1.4611 | 21.1987 | 18.8396 |
| 0.9532 | 1.86 | 16000 | 1.4429 | 21.4802 | 18.8239 |
| 0.6681 | 2.09 | 18000 | 1.5450 | 21.1981 | 18.6116 |
| 0.6971 | 2.32 | 20000 | 1.5516 | 21.3101 | 18.892 |
| 0.7283 | 2.55 | 22000 | 1.5405 | 20.902 | 18.6448 |
| 0.7308 | 2.78 | 24000 | 1.5363 | 21.3017 | 18.2578 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
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