|
--- |
|
language: |
|
- ko |
|
- zh |
|
base_model: facebook/mbart-large-50-many-to-many-mmt |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- bleu |
|
model-index: |
|
- name: tst-translation-output5 |
|
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-output5 |
|
|
|
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: 1.3149 |
|
- Bleu: 12.1284 |
|
- Gen Len: 15.2902 |
|
|
|
## 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 |
|
- total_train_batch_size: 16 |
|
- 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: 1500 |
|
- num_epochs: 40 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:| |
|
| 1.3822 | 0.86 | 2000 | 1.3693 | 8.4562 | 15.8491 | |
|
| 1.0081 | 1.71 | 4000 | 1.2806 | 11.3956 | 15.239 | |
|
| 0.7007 | 2.57 | 6000 | 1.3149 | 12.0444 | 15.34 | |
|
| 0.4483 | 3.43 | 8000 | 1.4177 | 11.5647 | 15.2139 | |
|
| 0.2837 | 4.29 | 10000 | 1.5126 | 11.1306 | 15.2984 | |
|
| 0.2276 | 5.14 | 12000 | 1.5938 | 11.1467 | 15.2992 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.0 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.14.0 |
|
|
