transformers pytorch mbart text2text-generation generated_from_trainer ko zh autotrain_compatible endpoints_compatible region:us
---
language:
- ko
- zh
base_model: ./reduced_model_zh
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: tst-translation-output2
  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-output2

This model is a fine-tuned version of [mbart-large-cc25](https://huggingface.co/facebook/mbart-large-cc25) on an custom dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4005
- Bleu: 26.0229
- Gen Len: 15.1659

## 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: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 4.5769        | 1.15  | 1000  | 4.0805          | 14.9483 | 30.0618 |
| 2.8098        | 2.31  | 2000  | 3.0612          | 19.7963 | 16.7121 |
| 1.7974        | 3.46  | 3000  | 2.8258          | 21.7059 | 15.5179 |
| 1.1474        | 4.62  | 4000  | 2.6951          | 22.4801 | 16.6382 |
| 0.8042        | 5.77  | 5000  | 2.7272          | 22.4419 | 15.1393 |
| 0.5605        | 6.93  | 6000  | 2.8239          | 23.1096 | 15.6457 |
| 0.3857        | 8.08  | 7000  | 2.9448          | 24.2536 | 15.1538 |
...
| 0.0042        | 40.42 | 35000 | 3.3485          | 25.2464 | 15.2387 |
| 0.0029        | 41.57 | 36000 | 3.3744          | 25.2885 | 15.1306 |
| 0.0026        | 42.73 | 37000 | 3.3947          | 25.9359 | 15.1896 |
| 0.0024        | 43.88 | 38000 | 3.3699          | 25.5309 | 15.2671 |
| 0.0022        | 45.03 | 39000 | 3.3947          | 25.2932 | 15.1387 |
| 0.0011        | 46.19 | 40000 | 3.4075          | 25.7551 | 15.1231 |
| 0.001         | 47.34 | 41000 | 3.3918          | 25.6345 | 15.1243 |
| 0.0007        | 48.5  | 42000 | 3.4063          | 25.7209 | 15.111  |
| 0.0006        | 49.65 | 43000 | 3.4003          | 25.9227 | 15.1873 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
