transformers pytorch 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 reduced embedding layer on an custom dataset.
It achieves the following results on the evaluation set:
- Loss: 5.5358
- Bleu: 19.1915
- Gen Len: 17.7756

## 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: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 35

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 1.1497        | 5.23  | 5000  | 3.8817          | 16.4877 | 18.2485 |
| 0.2561        | 10.46 | 10000 | 4.6013          | 17.9256 | 17.8049 |
| 0.0915        | 15.69 | 15000 | 4.9996          | 17.8722 | 18.1405 |
| 0.0436        | 20.92 | 20000 | 5.2561          | 19.0141 | 17.4316 |
| 0.0202        | 26.14 | 25000 | 5.4249          | 18.4325 | 18.2234 |
| 0.0087        | 31.37 | 30000 | 5.5129          | 18.9301 | 17.8334 |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
