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---
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
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