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---
library_name: transformers
license: cc-by-4.0
base_model: Helsinki-NLP/opus-mt-ru-en
tags:
- translation
- generated_from_trainer
metrics:
- bleu
model-index:
- name: tatoeba-ru-tok
results: []
language:
- ru
- tok
datasets:
- NetherQuartz/tatoeba-tokipona
---
<!-- 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. -->
# tatoeba-ru-tok
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ru-en](https://huggingface.co/Helsinki-NLP/opus-mt-ru-en) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5932
- Bleu: 47.6666
## 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: 64
- eval_batch_size: 64
- 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
- num_epochs: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 1.0515 | 1.0 | 1167 | 0.8539 | 37.3803 |
| 0.8186 | 2.0 | 2334 | 0.7284 | 41.5032 |
| 0.7002 | 3.0 | 3501 | 0.6803 | 43.5555 |
| 0.6501 | 4.0 | 4668 | 0.6485 | 45.0023 |
| 0.6091 | 5.0 | 5835 | 0.6302 | 45.6329 |
| 0.5778 | 6.0 | 7002 | 0.6180 | 45.8879 |
| 0.553 | 7.0 | 8169 | 0.6109 | 46.6945 |
| 0.533 | 8.0 | 9336 | 0.6041 | 46.6169 |
| 0.5128 | 9.0 | 10503 | 0.6002 | 47.0549 |
| 0.5015 | 10.0 | 11670 | 0.5961 | 47.2017 |
| 0.4851 | 11.0 | 12837 | 0.5962 | 47.5851 |
| 0.4795 | 12.0 | 14004 | 0.5939 | 47.5400 |
| 0.4659 | 13.0 | 15171 | 0.5932 | 47.6666 |
| 0.4608 | 14.0 | 16338 | 0.5939 | 47.6703 |
| 0.4593 | 15.0 | 17505 | 0.5936 | 47.6572 |
### Framework versions
- Transformers 4.52.4
- Pytorch 2.7.1+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1 |