transformers pytorch mbart text2text-generation generated_from_trainer en ko base_model:facebook/mbart-large-50-many-to-many-mmt autotrain_compatible endpoints_compatible region:us
---
language:
- en
- ko
base_model: facebook/mbart-large-50-many-to-many-mmt
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: enko_mbartLarge_36p_exp1
  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. -->

# enko_mbartLarge_36p_exp1

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: 1.2181
- Bleu: 15.4063
- Gen Len: 14.7808

## 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
- 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: 500
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 1.4235        | 0.46  | 5000  | 1.3893          | 12.3168 | 14.6634 |
| 1.3281        | 0.93  | 10000 | 1.2917          | 14.3522 | 14.9186 |
| 1.2506        | 1.39  | 15000 | 1.2669          | 14.3525 | 14.9494 |
| 1.1603        | 1.86  | 20000 | 1.2283          | 15.248  | 15.0062 |
| 1.0765        | 2.32  | 25000 | 1.2181          | 15.4063 | 14.7808 |
| 1.1019        | 2.79  | 30000 | 1.2753          | 14.3608 | 14.9014 |
| 1.0504        | 3.25  | 35000 | 1.2334          | 15.3253 | 14.7948 |
| 0.9431        | 3.72  | 40000 | 1.2512          | 15.2534 | 14.7293 |
| 0.8394        | 4.18  | 45000 | 1.2971          | 14.9999 | 14.7993 |


### Framework versions

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