tatoeba-tok-fr / README.md
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metadata
library_name: transformers
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-en-fr
tags:
  - translation
  - generated_from_trainer
metrics:
  - bleu
model-index:
  - name: tatoeba-tok-fr
    results: []
language:
  - tok
  - fr
datasets:
  - NetherQuartz/tatoeba-tokipona

tatoeba-tok-fr

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

  • Loss: 1.3544
  • Bleu: 23.4181

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
1.8608 1.0 1167 1.6433 13.4398
1.593 2.0 2334 1.5195 17.7658
1.4354 3.0 3501 1.4565 15.5366
1.3449 4.0 4668 1.4217 19.8814
1.2681 5.0 5835 1.4016 19.6534
1.2046 6.0 7002 1.3853 21.0562
1.1545 7.0 8169 1.3738 19.8606
1.1186 8.0 9336 1.3694 20.6401
1.0803 9.0 10503 1.3615 20.3338
1.0504 10.0 11670 1.3601 23.0924
1.021 11.0 12837 1.3570 22.4592
1.0041 12.0 14004 1.3547 22.5261
0.9865 13.0 15171 1.3546 23.0413
0.9706 14.0 16338 1.3544 23.1603
0.9658 15.0 17505 1.3548 23.7041

Framework versions

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