tatoeba-en-tok

This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-ru on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4513
  • Bleu: 49.2199

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
0.8381 1.0 1167 0.6677 38.6270
0.6401 2.0 2334 0.5611 42.8112
0.5453 3.0 3501 0.5228 44.9041
0.5046 4.0 4668 0.4977 46.2278
0.474 5.0 5835 0.4806 47.2086
0.4466 6.0 7002 0.4723 47.5220
0.4274 7.0 8169 0.4662 48.3719
0.4134 8.0 9336 0.4587 48.4629
0.3949 9.0 10503 0.4593 48.8579
0.3864 10.0 11670 0.4537 48.6287
0.375 11.0 12837 0.4546 48.8812
0.3692 12.0 14004 0.4522 49.1093
0.3608 13.0 15171 0.4524 49.1794
0.3553 14.0 16338 0.4513 49.2199
0.3533 15.0 17505 0.4518 49.2096

Framework versions

  • Transformers 4.52.4
  • Pytorch 2.7.1+cu128
  • Datasets 3.6.0
  • Tokenizers 0.21.1
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