transformers pytorch mbart text2text-generation generated_from_trainer ko ja base_model:facebook/mbart-large-50-many-to-many-mmt autotrain_compatible endpoints_compatible region:us
---
language:
- ko
- ja
base_model: facebook/mbart-large-50-many-to-many-mmt
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: mbartLarge_koja_37p_exp2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mbartLarge_koja_37p_exp2

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: 0.8988
- Bleu: 6.7577
- Gen Len: 17.8104

## 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: 350
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|
| 2.0622        | 0.11  | 1250  | 1.6679          | 1.2834 | 17.8009 |
| 1.5139        | 0.22  | 2500  | 1.4378          | 2.0427 | 17.8496 |
| 1.4121        | 0.33  | 3750  | 1.3116          | 2.7599 | 17.7667 |
| 1.2879        | 0.44  | 5000  | 1.2381          | 3.1444 | 17.8887 |
| 1.2344        | 0.55  | 6250  | 1.1769          | 3.3835 | 17.8323 |
| 1.1778        | 0.66  | 7500  | 1.1382          | 3.9511 | 17.4892 |
| 1.1461        | 0.77  | 8750  | 1.0938          | 3.9402 | 18.0136 |
| 1.1151        | 0.88  | 10000 | 1.0749          | 4.2134 | 18.0537 |
| 1.093         | 0.99  | 11250 | 1.0418          | 3.9587 | 17.8715 |
| 1.0626        | 1.1   | 12500 | 1.0315          | 4.6251 | 17.9406 |
| 1.0192        | 1.21  | 13750 | 1.0132          | 4.9573 | 18.1266 |
| 0.9957        | 1.32  | 15000 | 0.9989          | 4.3068 | 18.0925 |
| 0.9778        | 1.43  | 16250 | 0.9850          | 5.0517 | 17.8783 |
| 0.9446        | 1.54  | 17500 | 0.9748          | 5.0194 | 17.9348 |
| 0.9236        | 1.65  | 18750 | 0.9619          | 4.6011 | 17.7926 |
| 0.9091        | 1.76  | 20000 | 0.9564          | 4.6035 | 17.9399 |
| 0.9072        | 1.87  | 21250 | 0.9533          | 4.8313 | 17.6221 |
| 0.8758        | 1.98  | 22500 | 0.9421          | 5.2707 | 17.5851 |
| 0.8539        | 2.09  | 23750 | 0.9304          | 5.2661 | 17.821  |
| 0.8575        | 2.2   | 25000 | 0.9329          | 4.9143 | 17.8879 |
| 0.8314        | 2.31  | 26250 | 0.9262          | 5.106  | 18.0037 |
| 0.8248        | 2.42  | 27500 | 0.9241          | 5.3073 | 17.6632 |
| 0.8151        | 2.53  | 28750 | 0.9302          | 5.5675 | 17.7676 |
| 0.8093        | 2.64  | 30000 | 0.9149          | 6.2644 | 17.8475 |
| 0.7691        | 2.75  | 31250 | 0.8988          | 6.6682 | 17.7685 |
| 0.771         | 2.86  | 32500 | 0.9189          | 5.7856 | 17.8678 |
| 0.7658        | 2.97  | 33750 | 0.9175          | 6.2468 | 17.7313 |
| 0.7914        | 3.08  | 35000 | 0.9020          | 5.5525 | 17.7627 |
| 0.7264        | 3.19  | 36250 | 0.9046          | 6.2055 | 17.7662 |


### Framework versions

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