---
language:
- zh
- ko
base_model: facebook/mbart-large-cc25
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: zh-kr_mid
  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. -->

# zh-kr_mid

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: 2.5557
- Bleu: 16.6036
- Gen Len: 15.4901

## 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: 500
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 2.7248        | 0.75  | 1000  | 1.9410          | 3.2381  | 48.6095 |
| 1.5683        | 1.5   | 2000  | 1.6889          | 10.2345 | 20.4433 |
| 1.1916        | 2.25  | 3000  | 1.6843          | 13.4571 | 18.8854 |
| 1.068         | 2.99  | 4000  | 1.6390          | 15.6862 | 15.5054 |
| 0.7313        | 3.74  | 5000  | 1.7003          | 15.2014 | 16.5938 |
| 0.4832        | 4.49  | 6000  | 1.8982          | 15.0381 | 16.9068 |
| 0.3862        | 5.24  | 7000  | 2.1426          | 15.5397 | 15.6451 |
| 0.3675        | 5.99  | 8000  | 2.1168          | 15.8847 | 15.6926 |
| 0.2627        | 6.74  | 9000  | 2.2603          | 16.3603 | 15.9671 |
| 0.1955        | 7.49  | 10000 | 2.4114          | 15.7447 | 15.979  |
| 0.171         | 8.23  | 11000 | 2.5141          | 15.7852 | 15.9244 |
| 0.1702        | 8.98  | 12000 | 2.5557          | 16.6036 | 15.4901 |
| 0.1298        | 9.73  | 13000 | 2.6536          | 16.1319 | 15.5492 |
| 0.1052        | 10.48 | 14000 | 2.7586          | 16.1807 | 15.8884 |
| 0.2268        | 11.23 | 15000 | 2.7258          | 15.1752 | 15.5346 |
| 0.1327        | 11.98 | 16000 | 2.7193          | 15.8563 | 15.7971 |


### Framework versions

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