| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: Helsinki-NLP/opus-mt-es-es |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: esp_msl |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # esp_msl |
| |
| This model is a fine-tuned version of [Helsinki-NLP/opus-mt-es-es](https://huggingface.co/Helsinki-NLP/opus-mt-es-es) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2048 |
| - Model Preparation Time: 0.0048 |
| - Bleu Msl: 87.1599 |
| - Bleu Asl: 0 |
| - Ter Msl: 7.6997 |
| - Ter Asl: 100 |
| |
| ## 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: 1e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - optimizer: Use 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: 30 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Bleu Msl | Bleu Asl | Ter Msl | Ter Asl | |
| |:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------:|:--------:|:-------:|:-------:| |
| | No log | 1.0 | 75 | 3.9416 | 0.0048 | 9.6418 | 0 | 95.7604 | 100 | |
| | No log | 2.0 | 150 | 3.0683 | 0.0048 | 11.3858 | 0 | 98.1567 | 100 | |
| | No log | 3.0 | 225 | 2.5362 | 0.0048 | 19.3789 | 0 | 85.5300 | 100 | |
| | No log | 4.0 | 300 | 2.1286 | 0.0048 | 20.3180 | 0 | 83.8710 | 100 | |
| | No log | 5.0 | 375 | 1.8211 | 0.0048 | 17.8046 | 0 | 89.4931 | 100 | |
| | No log | 6.0 | 450 | 1.5708 | 0.0048 | 58.5580 | 0 | 29.5853 | 100 | |
| | 2.865 | 7.0 | 525 | 1.3571 | 0.0048 | 63.7680 | 0 | 24.7005 | 100 | |
| | 2.865 | 8.0 | 600 | 1.1614 | 0.0048 | 65.7864 | 0 | 21.8433 | 100 | |
| | 2.865 | 9.0 | 675 | 0.9983 | 0.0048 | 57.8092 | 0 | 23.8710 | 100 | |
| | 2.865 | 10.0 | 750 | 0.8741 | 0.0048 | 65.5640 | 0 | 21.2903 | 100 | |
| | 2.865 | 11.0 | 825 | 0.7724 | 0.0048 | 69.4951 | 0 | 19.3548 | 100 | |
| | 2.865 | 12.0 | 900 | 0.6838 | 0.0048 | 74.3444 | 0 | 16.8664 | 100 | |
| | 2.865 | 13.0 | 975 | 0.6211 | 0.0048 | 71.7643 | 0 | 17.6959 | 100 | |
| | 0.8947 | 14.0 | 1050 | 0.5723 | 0.0048 | 75.2869 | 0 | 15.8525 | 100 | |
| | 0.8947 | 15.0 | 1125 | 0.5436 | 0.0048 | 75.9376 | 0 | 15.2995 | 100 | |
| | 0.8947 | 16.0 | 1200 | 0.5171 | 0.0048 | 60.9052 | 0 | 19.8157 | 100 | |
| | 0.8947 | 17.0 | 1275 | 0.4969 | 0.0048 | 76.2738 | 0 | 14.1935 | 100 | |
| | 0.8947 | 18.0 | 1350 | 0.4818 | 0.0048 | 76.5583 | 0 | 14.1935 | 100 | |
| | 0.8947 | 19.0 | 1425 | 0.4685 | 0.0048 | 76.8689 | 0 | 14.3779 | 100 | |
| | 0.3654 | 20.0 | 1500 | 0.4626 | 0.0048 | 77.2378 | 0 | 13.8249 | 100 | |
| | 0.3654 | 21.0 | 1575 | 0.4511 | 0.0048 | 76.4648 | 0 | 14.0092 | 100 | |
| | 0.3654 | 22.0 | 1650 | 0.4480 | 0.0048 | 76.3980 | 0 | 13.9171 | 100 | |
| | 0.3654 | 23.0 | 1725 | 0.4454 | 0.0048 | 77.1739 | 0 | 13.6406 | 100 | |
| | 0.3654 | 24.0 | 1800 | 0.4380 | 0.0048 | 77.3622 | 0 | 13.7327 | 100 | |
| | 0.3654 | 25.0 | 1875 | 0.4342 | 0.0048 | 75.8442 | 0 | 14.1935 | 100 | |
| | 0.3654 | 26.0 | 1950 | 0.4346 | 0.0048 | 77.4371 | 0 | 13.7327 | 100 | |
| | 0.2434 | 27.0 | 2025 | 0.4321 | 0.0048 | 78.0849 | 0 | 13.6406 | 100 | |
| | 0.2434 | 28.0 | 2100 | 0.4312 | 0.0048 | 77.8954 | 0 | 13.6406 | 100 | |
| | 0.2434 | 29.0 | 2175 | 0.4300 | 0.0048 | 77.7089 | 0 | 13.7327 | 100 | |
| | 0.2434 | 30.0 | 2250 | 0.4297 | 0.0048 | 77.7089 | 0 | 13.7327 | 100 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.46.2 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.20.3 |
| |
