|
--- |
|
language: |
|
- ko |
|
- en |
|
base_model: facebook/mbart-large-50-many-to-many-mmt |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- bleu |
|
model-index: |
|
- name: ko-en_mbartLarge_exp20p_linear_decay |
|
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. --> |
|
|
|
# ko-en_mbartLarge_exp20p_linear_decay |
|
|
|
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: 1.2291 |
|
- Bleu: 26.9332 |
|
- Gen Len: 18.743 |
|
|
|
## 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: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:| |
|
| 1.4396 | 0.23 | 1000 | 1.3815 | 21.7052 | 18.6047 | |
|
| 1.338 | 0.46 | 2000 | 1.3044 | 23.7087 | 18.9939 | |
|
| 1.2938 | 0.7 | 3000 | 1.2556 | 24.6339 | 18.8866 | |
|
| 1.251 | 0.93 | 4000 | 1.2229 | 25.2975 | 19.0918 | |
|
| 0.9843 | 1.16 | 5000 | 1.2309 | 25.609 | 18.7589 | |
|
| 0.9874 | 1.39 | 6000 | 1.2101 | 26.1792 | 18.8287 | |
|
| 0.9838 | 1.62 | 7000 | 1.2053 | 26.024 | 18.4025 | |
|
| 0.9927 | 1.86 | 8000 | 1.1907 | 26.3148 | 19.09 | |
|
| 0.7835 | 2.09 | 9000 | 1.2300 | 26.5613 | 18.7196 | |
|
| 0.7437 | 2.32 | 10000 | 1.2358 | 26.8232 | 18.6513 | |
|
| 0.7585 | 2.55 | 11000 | 1.2291 | 26.9203 | 18.7513 | |
|
| 0.7631 | 2.78 | 12000 | 1.2170 | 26.8668 | 18.5441 | |
|
| 0.7428 | 3.02 | 13000 | 1.3272 | 26.2506 | 18.6959 | |
|
| 0.5502 | 3.25 | 14000 | 1.3392 | 26.419 | 18.6722 | |
|
| 0.5577 | 3.48 | 15000 | 1.3204 | 26.1621 | 18.7036 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.0 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.14.1 |
|
|
