transformers safetensors mbart text2text-generation generated_from_trainer zh ko base_model:facebook/mbart-large-50-many-to-many-mmt autotrain_compatible endpoints_compatible region:us
---
language:
- zh
- ko
base_model: facebook/mbart-large-50-many-to-many-mmt
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: zhko_mbartLarge_100p_run1
  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. -->

# zhko_mbartLarge_100p_run1

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: 0.7819
- Bleu: 45.7383
- Gen Len: 13.0535

## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|
| 1.0208        | 1.0   | 69443  | 0.8814          | 41.5541 | 13.044  |
| 0.8756        | 2.0   | 138887 | 0.8034          | 44.6906 | 13.1329 |
| 0.7566        | 3.0   | 208330 | 0.7819          | 45.7383 | 13.0535 |
| 0.6239        | 4.0   | 277774 | 0.7928          | 46.5398 | 12.9925 |
| 0.5245        | 5.0   | 347217 | 0.8333          | 46.9153 | 13.0368 |
| 0.4333        | 6.0   | 416661 | 0.8993          | 46.5833 | 12.9999 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
