transformers pytorch safetensors mbart text2text-generation generated_from_trainer ko en autotrain_compatible endpoints_compatible region:us
---
base_model: ./reduced_model
language:
- ko
- en
metrics:
- bleu
tags:
- generated_from_trainer
model-index:
- name: tst-translation-output
  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-output

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: 3.7663
- Bleu: 19.3382
- Gen Len: 17.8929

## 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: 16
- total_train_batch_size: 128
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 2.6161        | 11.09 | 2000 | 3.1762          | 13.5109 | 19.1966 |
| 2.6161        | 13.86 | 2500 | 3.0375          | 16.2868 | 18.7985 |
| 1.4467        | 16.62 | 3000 | 3.1328          | 17.6991 | 18.1949 |
| 1.4467        | 19.39 | 3500 | 3.2690          | 17.9052 | 18.3117 |
| 0.6809        | 22.15 | 4000 | 3.3850          | 18.4075 | 18.2149 |
| 0.6809        | 24.91 | 4500 | 3.4465          | 19.0339 | 18.009  |
| 0.3422        | 27.68 | 5000 | 3.5680          | 18.7281 | 17.5902 |
| 0.3422        | 30.44 | 5500 | 3.6350          | 19.1534 | 18.2177 |
| 0.1941        | 33.2  | 6000 | 3.7153          | 19.2575 | 17.8784 |
| 0.1941        | 35.97 | 6500 | 3.7382          | 19.2475 | 17.9831 |
| 0.1271        | 38.73 | 7000 | 3.7573          | 19.3045 | 17.9889 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
