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vania2911/exp5_10partition_modelo_asl9000
exp5_10partition_modelo_asl9000 is a machine learning model from vania2911. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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From the Hugging Face model README
This model is a fine-tuned version of Helsinki-NLP/opus-mt-es-es on the None dataset. It achieves the following results on the evaluation set:
More information needed
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More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Bleu Msl | Bleu 1 Msl | Bleu 2 Msl | Bleu 3 Msl | Bleu 4 Msl | Ter Msl | Bleu Asl | Bleu 1 Asl | Bleu 2 Asl | Bleu 3 Asl | Bleu 4 Asl | Ter Asl |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 225 | 0.1402 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9571 | 0.9302 | 0.9016 | 0.8690 | 5.2217 |
| No log | 2.0 | 450 | 0.1092 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9671 | 0.9451 | 0.9202 | 0.8905 | 3.9409 |
| 0.2823 | 3.0 | 675 | 0.0958 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9742 | 0.9559 | 0.9339 | 0.9076 | 3.1034 |
| 0.2823 | 4.0 | 900 | 0.0995 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9722 | 0.9531 | 0.9312 | 0.9050 | 3.3744 |
| 0.0497 | 5.0 | 1125 | 0.1036 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9740 | 0.9555 | 0.9335 | 0.9075 | 3.2020 |
| 0.0497 | 6.0 | 1350 | 0.0950 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9748 | 0.9574 | 0.9371 | 0.9129 | 2.9064 |
| 0.025 | 7.0 | 1575 | 0.0952 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9752 | 0.9592 | 0.9393 | 0.9155 | 2.9064 |
| 0.025 | 8.0 | 1800 | 0.0997 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9783 | 0.9630 | 0.9444 | 0.9211 | 2.7094 |
| 0.0153 | 9.0 | 2025 | 0.0957 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9785 | 0.9627 | 0.9441 | 0.9214 | 2.4877 |
| 0.0153 | 10.0 | 2250 | 0.0923 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9783 | 0.9622 | 0.9429 | 0.9198 | 2.6108 |
| 0.0153 | 11.0 | 2475 | 0.0963 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9783 | 0.9619 | 0.9429 | 0.9200 | 2.6108 |
| 0.0118 | 12.0 | 2700 | 0.0957 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9800 | 0.9643 | 0.9458 | 0.9233 | 2.5369 |
| 0.0118 | 13.0 | 2925 | 0.0988 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9798 | 0.9641 | 0.9451 | 0.9222 | 2.4631 |
| 0.009 | 14.0 | 3150 | 0.1050 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9796 | 0.9637 | 0.9445 | 0.9212 | 2.5369 |
| 0.009 | 15.0 | 3375 | 0.0975 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9817 | 0.9670 | 0.9489 | 0.9269 | 2.2167 |
| 0.0063 | 16.0 | 3600 | 0.1001 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9800 | 0.9654 | 0.9474 | 0.9255 | 2.4138 |
| 0.0063 | 17.0 | 3825 | 0.1015 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9774 | 0.9623 | 0.9446 | 0.9226 | 2.5616 |
| 0.0058 | 18.0 | 4050 | 0.1012 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9798 | 0.9645 | 0.9461 | 0.9236 | 2.3892 |
| 0.0058 | 19.0 | 4275 | 0.0994 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9793 | 0.9645 | 0.9466 | 0.9249 | 2.5369 |
| 0.0038 | 20.0 | 4500 | 0.0988 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9795 | 0.9642 | 0.9460 | 0.9235 | 2.4384 |
| 0.0038 | 21.0 | 4725 | 0.0980 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9804 | 0.9654 | 0.9474 | 0.9253 | 2.3399 |
| 0.0038 | 22.0 | 4950 | 0.0983 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9806 | 0.9658 | 0.9482 | 0.9268 | 2.3645 |
| 0.003 | 23.0 | 5175 | 0.0985 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9804 | 0.9654 | 0.9475 | 0.9255 | 2.3645 |
| 0.003 | 24.0 | 5400 | 0.0998 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9806 | 0.9659 | 0.9486 | 0.9270 | 2.2906 |
| 0.0021 | 25.0 | 5625 | 0.0992 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9802 | 0.9653 | 0.9480 | 0.9265 | 2.4138 |
| 0.0021 | 26.0 | 5850 | 0.1014 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9806 | 0.9658 | 0.9481 | 0.9265 | 2.3399 |
| 0.0016 | 27.0 | 6075 | 0.1003 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9808 | 0.9663 | 0.9490 | 0.9274 | 2.2660 |
| 0.0016 | 28.0 | 6300 | 0.0990 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9806 | 0.9661 | 0.9488 | 0.9274 | 2.3399 |
| 0.0017 | 29.0 | 6525 | 0.1000 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9802 | 0.9653 | 0.9477 | 0.9260 | 2.3892 |
| 0.0017 | 30.0 | 6750 | 0.1008 | 0.0034 | 0 | 0 | 0 | 0 | 0 | 100 | 0 | 0.9800 | 0.9650 | 0.9472 | 0.9254 | 2.4138 |