|
|
--- |
|
|
library_name: transformers |
|
|
language: |
|
|
- nan |
|
|
license: apache-2.0 |
|
|
base_model: Helsinki-NLP/opus-mt-en-ZH |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
datasets: |
|
|
- mozilla-foundation/common_voice_17_0 |
|
|
metrics: |
|
|
- bleu |
|
|
model-index: |
|
|
- name: helsinki_new_ver3 |
|
|
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. --> |
|
|
|
|
|
# helsinki_new_ver3 |
|
|
|
|
|
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ZH](https://huggingface.co/Helsinki-NLP/opus-mt-en-ZH) on the mozilla-foundation/common_voice_17_0 dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.7044 |
|
|
- Bleu: 2.2015 |
|
|
|
|
|
## 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: 1e-06 |
|
|
- train_batch_size: 8 |
|
|
- eval_batch_size: 8 |
|
|
- seed: 42 |
|
|
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: linear |
|
|
- lr_scheduler_warmup_steps: 1000 |
|
|
- training_steps: 23000 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Bleu | |
|
|
|:-------------:|:-----:|:-----:|:---------------:|:------:| |
|
|
| 0.9675 | 0.32 | 1000 | 1.0573 | 0.7690 | |
|
|
| 0.9217 | 0.64 | 2000 | 0.9924 | 1.3531 | |
|
|
| 0.8782 | 0.96 | 3000 | 0.9463 | 1.8407 | |
|
|
| 0.8377 | 1.28 | 4000 | 0.9078 | 3.0190 | |
|
|
| 0.8304 | 1.6 | 5000 | 0.8765 | 2.1759 | |
|
|
| 0.8114 | 1.92 | 6000 | 0.8479 | 3.2072 | |
|
|
| 0.7735 | 2.24 | 7000 | 0.8247 | 4.0669 | |
|
|
| 0.7667 | 2.56 | 8000 | 0.8051 | 5.6676 | |
|
|
| 0.7547 | 2.88 | 9000 | 0.7882 | 4.2755 | |
|
|
| 0.7151 | 3.2 | 10000 | 0.7712 | 5.7800 | |
|
|
| 0.7103 | 3.52 | 11000 | 0.7591 | 6.0659 | |
|
|
| 0.7095 | 3.84 | 12000 | 0.7458 | 7.0038 | |
|
|
| 0.7044 | 4.16 | 13000 | 0.7351 | 1.7120 | |
|
|
| 0.6717 | 4.48 | 14000 | 0.7250 | 8.0104 | |
|
|
| 0.6856 | 4.8 | 15000 | 0.7169 | 2.1741 | |
|
|
| 0.6755 | 5.12 | 16000 | 0.7097 | 2.1614 | |
|
|
| 0.6635 | 5.44 | 17000 | 0.7044 | 2.2015 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.51.3 |
|
|
- Pytorch 2.6.0+cu124 |
|
|
- Datasets 3.5.1 |
|
|
- Tokenizers 0.21.1 |
|
|
|
