transformers pytorch mbart text2text-generation generated_from_trainer ko zh base_model:facebook/mbart-large-cc25 base_model:finetune:facebook/mbart-large-cc25 autotrain_compatible endpoints_compatible region:us
---
base_model: facebook/mbart-large-cc25
language:
- ko
- zh
metrics:
- bleu
tags:
- generated_from_trainer
model-index:
- name: tst-translation-output4
  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-output4

This model is a fine-tuned version of [facebook/mbart-large-cc25](https://huggingface.co/facebook/mbart-large-cc25) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3569
- Bleu: 11.508
- Gen Len: 14.3854

## 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: 1500
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 1.5428        | 0.86  | 2000  | 1.4469          | 8.6101  | 16.9959 |
| 1.1195        | 1.71  | 4000  | 1.3471          | 10.3699 | 14.5055 |
| 0.8028        | 2.57  | 6000  | 1.3569          | 11.508  | 14.3955 |
| 0.5856        | 3.43  | 8000  | 1.4776          | 10.7663 | 15.0208 |
| 0.378         | 4.29  | 10000 | 1.6134          | 10.5237 | 14.3284 |
| 0.3093        | 5.14  | 12000 | 1.7701          | 10.7522 | 14.0819 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0
