transformers pytorch 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_19p_run3
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# zhko_mbartLarge_19p_run3

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: 1.4430
- Bleu: 17.067
- Gen Len: 14.7398

## 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: 3.5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 1.957         | 0.45  | 1250  | 1.7573          | 12.1283 | 15.4356 |
| 1.6568        | 0.9   | 2500  | 1.5793          | 14.3528 | 14.9632 |
| 1.4964        | 1.35  | 3750  | 1.4806          | 16.0215 | 14.9365 |
| 1.2204        | 1.79  | 5000  | 1.4682          | 16.5619 | 14.8621 |
| 1.1678        | 2.24  | 6250  | 1.4430          | 16.9926 | 14.7721 |
| 0.9448        | 2.69  | 7500  | 1.4615          | 17.0327 | 14.5641 |
| 0.9083        | 3.14  | 8750  | 1.4744          | 17.863  | 14.6946 |
| 0.7389        | 3.59  | 10000 | 1.5129          | 17.3256 | 14.7824 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
