Gopal-finetuned-custom-en-to-ru
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-ru on an unknown dataset.
Model description
This is the model fine tuned by me on my custom dataset, the dataset contains communication domain parallel corpuses.
Intended uses & limitations
This model is used for customised purposes and people are advised to fine tune it on the basis of there requirement
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 200
- mixed_precision_training: Native AMP
Training results
The bleu score: 31.08
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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