|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- bleu |
|
model-index: |
|
- name: opus-mt-en-ru-finetuned-en-to-ru-Legal |
|
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. --> |
|
|
|
# opus-mt-en-ru-finetuned-en-to-ru-Legal |
|
|
|
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ru](https://huggingface.co/Helsinki-NLP/opus-mt-en-ru) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.8561 |
|
- Bleu: 46.7284 |
|
- Gen Len: 23.1317 |
|
|
|
## 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: 2e-05 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:| |
|
| No log | 1.0 | 387 | 1.1719 | 34.0562 | 22.991 | |
|
| 1.524 | 2.0 | 774 | 1.0342 | 37.7233 | 23.0052 | |
|
| 1.0226 | 3.0 | 1161 | 0.9595 | 40.0983 | 22.9755 | |
|
| 0.8066 | 4.0 | 1548 | 0.9188 | 41.9634 | 23.1162 | |
|
| 0.8066 | 5.0 | 1935 | 0.8907 | 43.6537 | 23.0923 | |
|
| 0.6637 | 6.0 | 2322 | 0.8771 | 44.5208 | 23.1097 | |
|
| 0.5697 | 7.0 | 2709 | 0.8669 | 45.5589 | 23.1388 | |
|
| 0.5175 | 8.0 | 3096 | 0.8603 | 46.2211 | 23.2356 | |
|
| 0.5175 | 9.0 | 3483 | 0.8566 | 46.7201 | 23.1375 | |
|
| 0.4768 | 10.0 | 3870 | 0.8561 | 46.7284 | 23.1317 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.13.0 |
|
- Pytorch 1.12.0 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.10.3 |
|
|