--- library_name: transformers license: apache-2.0 base_model: Helsinki-NLP/opus-mt-es-fr tags: - translation - generated_from_trainer datasets: - tatoeba metrics: - bleu model-index: - name: finetuned-tatoeba-es-to-fr results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: tatoeba type: tatoeba config: es-fr split: train args: es-fr metrics: - name: Bleu type: bleu value: 61.270637255337 --- # finetuned-tatoeba-es-to-fr This model is a fine-tuned version of [Helsinki-NLP/opus-mt-es-fr](https://huggingface.co/Helsinki-NLP/opus-mt-es-fr) on the tatoeba dataset. It achieves the following results on the evaluation set: - Loss: 0.4412 - Model Preparation Time: 0.0198 - Bleu: 61.2706 ## 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: 32 - 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: 5 - mixed_precision_training: Native AMP ### Training results ### Framework versions - Transformers 4.48.3 - Pytorch 2.5.1+cu124 - Datasets 3.3.2 - Tokenizers 0.21.0