| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: Helsinki-NLP/opus-mt-es-es |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: 2120mslsamples |
| 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. --> |
|
|
| # 2120mslsamples |
|
|
| 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: 0.4982 |
| - Bleu Msl: 79.5487 |
| - Bleu Asl: 0 |
| - Ter Msl: 11.4533 |
| - 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: 0.0001 |
| - 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: 30 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Bleu Msl | Bleu Asl | Ter Msl | Ter Asl | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-------:|:-------:| |
| | No log | 1.0 | 67 | 1.0924 | 16.5734 | 0 | 78.3784 | 100 | |
| | No log | 2.0 | 134 | 0.5283 | 66.9864 | 0 | 17.2037 | 100 | |
| | No log | 3.0 | 201 | 0.4500 | 32.7340 | 0 | 24.8960 | 100 | |
| | No log | 4.0 | 268 | 0.4546 | 64.2241 | 0 | 17.0998 | 100 | |
| | No log | 5.0 | 335 | 0.4371 | 79.5661 | 0 | 12.3181 | 100 | |
| | No log | 6.0 | 402 | 0.4183 | 62.3356 | 0 | 12.4740 | 100 | |
| | No log | 7.0 | 469 | 0.4174 | 78.8409 | 0 | 12.2141 | 100 | |
| | 0.5741 | 8.0 | 536 | 0.4236 | 73.4058 | 0 | 13.0977 | 100 | |
| | 0.5741 | 9.0 | 603 | 0.4365 | 80.4263 | 0 | 11.6424 | 100 | |
| | 0.5741 | 10.0 | 670 | 0.4230 | 78.2192 | 0 | 11.5904 | 100 | |
| | 0.5741 | 11.0 | 737 | 0.4461 | 81.5222 | 0 | 11.0187 | 100 | |
| | 0.5741 | 12.0 | 804 | 0.4361 | 81.0763 | 0 | 10.8108 | 100 | |
| | 0.5741 | 13.0 | 871 | 0.4462 | 80.2271 | 0 | 11.4345 | 100 | |
| | 0.5741 | 14.0 | 938 | 0.4487 | 81.2932 | 0 | 10.0832 | 100 | |
| | 0.0399 | 15.0 | 1005 | 0.4535 | 82.0574 | 0 | 10.1351 | 100 | |
| | 0.0399 | 16.0 | 1072 | 0.4561 | 81.1900 | 0 | 10.7069 | 100 | |
| | 0.0399 | 17.0 | 1139 | 0.4498 | 80.5848 | 0 | 10.3430 | 100 | |
| | 0.0399 | 18.0 | 1206 | 0.4704 | 81.2086 | 0 | 10.4470 | 100 | |
| | 0.0399 | 19.0 | 1273 | 0.4780 | 83.3481 | 0 | 9.7713 | 100 | |
| | 0.0399 | 20.0 | 1340 | 0.4697 | 82.5737 | 0 | 9.8753 | 100 | |
| | 0.0399 | 21.0 | 1407 | 0.4675 | 82.5187 | 0 | 9.8753 | 100 | |
| | 0.0399 | 22.0 | 1474 | 0.4678 | 82.9501 | 0 | 10.0312 | 100 | |
| | 0.0155 | 23.0 | 1541 | 0.4708 | 82.3160 | 0 | 9.9792 | 100 | |
| | 0.0155 | 24.0 | 1608 | 0.4732 | 82.1759 | 0 | 10.0832 | 100 | |
| | 0.0155 | 25.0 | 1675 | 0.4777 | 82.5015 | 0 | 9.8233 | 100 | |
| | 0.0155 | 26.0 | 1742 | 0.4723 | 81.7682 | 0 | 10.1351 | 100 | |
| | 0.0155 | 27.0 | 1809 | 0.4755 | 82.1104 | 0 | 9.9792 | 100 | |
| | 0.0155 | 28.0 | 1876 | 0.4763 | 82.2547 | 0 | 10.1351 | 100 | |
| | 0.0155 | 29.0 | 1943 | 0.4756 | 82.2633 | 0 | 10.0832 | 100 | |
| | 0.01 | 30.0 | 2010 | 0.4761 | 82.2721 | 0 | 10.0312 | 100 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.49.0 |
| - Pytorch 2.5.1+cu124 |
| - Datasets 3.3.2 |
| - Tokenizers 0.21.0 |
|
|
