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vania2911/exp5_10partition_modelo12000
exp5_10partition_modelo12000 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 | 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 | 300 | 0.4552 | 84.0896 | 0.0867 | 0.0054 | 0.0023 | 0.0013 | 717.8919 | 0.0 | 0.5744 | 0.0080 | 0.0020 | 0.0009 | 7.3645 |
| 0.4443 | 2.0 | 600 | 0.3655 | 100.0000 | 0.1033 | 0.0059 | 0.0024 | 0.0014 | 57.2188 | 0.0 | 0.5856 | 0.0081 | 0.0021 | 0.0009 | 6.3300 |
| 0.4443 | 3.0 | 900 | 0.3487 | 59.4604 | 0.1333 | 0.0067 | 0.0026 | 0.0015 | 78.8308 | 0.0 | 0.5989 | 0.0082 | 0.0021 | 0.0010 | 6.6010 |
| 0.0984 | 4.0 | 1200 | 0.3369 | 100.0000 | 0.1600 | 0.0073 | 0.0028 | 0.0016 | 48.8043 | 0.0 | 0.5856 | 0.0081 | 0.0021 | 0.0009 | 7.0936 |
| 0.0592 | 5.0 | 1500 | 0.3564 | 23.3569 | 0.1433 | 0.0069 | 0.0027 | 0.0015 | 54.2073 | 0.0 | 0.5133 | 0.0076 | 0.0020 | 0.0009 | 10.7882 |
| 0.0592 | 6.0 | 1800 | 0.3252 | 100.0000 | 0.2033 | 0.0082 | 0.0030 | 0.0017 | 50.3986 | 0.0 | 0.5233 | 0.0076 | 0.0020 | 0.0009 | 9.8768 |
| 0.0357 | 7.0 | 2100 | 0.3320 | 70.7107 | 0.1733 | 0.0076 | 0.0029 | 0.0016 | 51.7272 | 0.0 | 0.5533 | 0.0078 | 0.0020 | 0.0009 | 8.1034 |
| 0.0357 | 8.0 | 2400 | 0.3809 | 50.0000 | 0.1200 | 0.0063 | 0.0025 | 0.0015 | 56.5102 | 0.0 | 0.5544 | 0.0079 | 0.0020 | 0.0009 | 8.9655 |
| 0.0268 | 9.0 | 2700 | 0.2994 | 28.9178 | 0.2167 | 0.0085 | 0.0031 | 0.0017 | 53.2329 | 0.0 | 0.5189 | 0.0076 | 0.0020 | 0.0009 | 10.4680 |
| 0.02 | 10.0 | 3000 | 0.3532 | 45.1801 | 0.2033 | 0.0082 | 0.0030 | 0.0017 | 55.0044 | 0.0 | 0.5544 | 0.0079 | 0.0020 | 0.0009 | 9.1872 |
| 0.02 | 11.0 | 3300 | 0.3183 | 66.8740 | 0.19 | 0.0080 | 0.0029 | 0.0016 | 50.3100 | 0.0 | 0.4822 | 0.0073 | 0.0019 | 0.0009 | 14.1626 |
| 0.0172 | 12.0 | 3600 | 0.3428 | 66.8740 | 0.2333 | 0.0088 | 0.0031 | 0.0017 | 43.5784 | 0.0 | 0.5133 | 0.0076 | 0.0020 | 0.0009 | 10.3941 |
| 0.0172 | 13.0 | 3900 | 0.3094 | 45.1801 | 0.25 | 0.0091 | 0.0032 | 0.0018 | 45.2613 | 0.0 | 0.4867 | 0.0074 | 0.0019 | 0.0009 | 11.1576 |
| 0.0138 | 14.0 | 4200 | 0.3183 | 100.0000 | 0.2767 | 0.0096 | 0.0033 | 0.0018 | 36.5810 | 0.0 | 0.5189 | 0.0076 | 0.0020 | 0.0009 | 10.1970 |
| 0.0114 | 15.0 | 4500 | 0.3215 | 100.0000 | 0.28 | 0.0097 | 0.0033 | 0.0018 | 49.6014 | 0.0 | 0.5656 | 0.0079 | 0.0020 | 0.0009 | 7.8818 |
| 0.0114 | 16.0 | 4800 | 0.3028 | 66.8740 | 0.27 | 0.0095 | 0.0033 | 0.0018 | 37.8211 | 0.0 | 0.5156 | 0.0076 | 0.0020 | 0.0009 | 9.8522 |
| 0.0086 | 17.0 | 5100 | 0.3086 | 100.0000 | 0.27 | 0.0095 | 0.0033 | 0.0018 | 51.0186 | 0.0 | 0.5278 | 0.0077 | 0.0020 | 0.0009 | 8.6946 |
| 0.0086 | 18.0 | 5400 | 0.3301 | 66.8740 | 0.22 | 0.0086 | 0.0031 | 0.0017 | 50.3100 | 0.0 | 0.5256 | 0.0076 | 0.0020 | 0.0009 | 9.2118 |
| 0.0078 | 19.0 | 5700 | 0.3219 | 100.0000 | 0.2533 | 0.0092 | 0.0032 | 0.0018 | 41.8069 | 0.0 | 0.5256 | 0.0076 | 0.0020 | 0.0009 | 10.2463 |
| 0.0067 | 20.0 | 6000 | 0.3188 | 100.0000 | 0.2367 | 0.0089 | 0.0032 | 0.0017 | 48.0957 | 0.0 | 0.4744 | 0.0073 | 0.0019 | 0.0009 | 12.3153 |
| 0.0067 | 21.0 | 6300 | 0.3144 | 100.0000 | 0.26 | 0.0093 | 0.0033 | 0.0018 | 44.5527 | 0.0 | 0.5444 | 0.0078 | 0.0020 | 0.0009 | 8.4729 |
| 0.0056 | 22.0 | 6600 | 0.3121 | 100.0000 | 0.2667 | 0.0094 | 0.0033 | 0.0018 | 50.8415 | 0.0 | 0.5767 | 0.0080 | 0.0021 | 0.0009 | 7.2167 |
| 0.0056 | 23.0 | 6900 | 0.3140 | 23.3569 | 0.24 | 0.0090 | 0.0032 | 0.0017 | 46.6785 | 0.0 | 0.5844 | 0.0081 | 0.0021 | 0.0009 | 6.8473 |
| 0.0043 | 24.0 | 7200 | 0.3258 | 100.0000 | 0.2567 | 0.0093 | 0.0032 | 0.0018 | 44.4641 | 0.0 | 0.58 | 0.0080 | 0.0021 | 0.0009 | 7.6355 |
| 0.0039 | 25.0 | 7500 | 0.3072 | 23.3569 | 0.2333 | 0.0088 | 0.0031 | 0.0017 | 48.0071 | 0.0 | 0.5667 | 0.0079 | 0.0020 | 0.0009 | 8.3005 |
| 0.0039 | 26.0 | 7800 | 0.3147 | 23.3569 | 0.22 | 0.0086 | 0.0031 | 0.0017 | 48.3614 | 0.0 | 0.5689 | 0.0080 | 0.0020 | 0.0009 | 7.5369 |
| 0.0028 | 27.0 | 8100 | 0.3168 | 35.9304 | 0.2233 | 0.0086 | 0.0031 | 0.0017 | 45.9699 | 0.0 | 0.5567 | 0.0079 | 0.0020 | 0.0009 | 8.2020 |
| 0.0028 | 28.0 | 8400 | 0.3123 | 23.3569 | 0.23 | 0.0088 | 0.0031 | 0.0017 | 46.1470 | 0.0 | 0.5489 | 0.0078 | 0.0020 | 0.0009 | 8.6207 |
| 0.0024 | 29.0 | 8700 | 0.3166 | 23.3569 | 0.2333 | 0.0088 | 0.0031 | 0.0017 | 46.2356 | 0.0 | 0.5367 | 0.0077 | 0.0020 | 0.0009 | 9.6552 |
| 0.0025 | 30.0 | 9000 | 0.3170 | 23.3569 | 0.2333 | 0.0088 | 0.0031 | 0.0017 | 46.9442 | 0.0 | 0.5367 | 0.0077 | 0.0020 | 0.0009 | 9.6305 |