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--- |
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license: apache-2.0 |
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base_model: Helsinki-NLP/opus-mt-en-es |
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tags: |
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- generated_from_trainer |
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metrics: |
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- bleu |
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model-index: |
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- name: opus-mt-en-es-finetuned-es-to-pbb-v0.1 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# opus-mt-en-es-finetuned-es-to-pbb-v0.1 |
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-es](https://huggingface.co/Helsinki-NLP/opus-mt-en-es) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9576 |
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- Bleu: 5.2917 |
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- Gen Len: 76.1652 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:| |
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| No log | 1.0 | 194 | 1.5013 | 4.5843 | 75.6652 | |
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| No log | 2.0 | 388 | 1.5089 | 4.6332 | 74.3943 | |
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| 0.6987 | 3.0 | 582 | 1.5167 | 4.6474 | 76.8423 | |
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| 0.6987 | 4.0 | 776 | 1.5170 | 4.8581 | 75.5565 | |
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| 0.6987 | 5.0 | 970 | 1.5234 | 4.7496 | 75.4673 | |
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| 0.6711 | 6.0 | 1164 | 1.5304 | 4.7982 | 74.4077 | |
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| 0.6711 | 7.0 | 1358 | 1.5285 | 4.8994 | 75.1533 | |
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| 0.6426 | 8.0 | 1552 | 1.5354 | 4.7699 | 74.7217 | |
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| 0.6426 | 9.0 | 1746 | 1.5481 | 5.0032 | 75.0938 | |
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| 0.6426 | 10.0 | 1940 | 1.5543 | 4.6445 | 75.4301 | |
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| 0.616 | 11.0 | 2134 | 1.5606 | 5.023 | 75.744 | |
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| 0.616 | 12.0 | 2328 | 1.5647 | 4.9297 | 75.2812 | |
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| 0.5893 | 13.0 | 2522 | 1.5650 | 5.082 | 76.2872 | |
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| 0.5893 | 14.0 | 2716 | 1.5794 | 4.9381 | 76.0521 | |
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| 0.5893 | 15.0 | 2910 | 1.5852 | 4.4323 | 74.2783 | |
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| 0.5614 | 16.0 | 3104 | 1.5895 | 4.8884 | 74.1042 | |
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| 0.5614 | 17.0 | 3298 | 1.5993 | 4.73 | 76.7842 | |
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| 0.5614 | 18.0 | 3492 | 1.6051 | 4.8878 | 74.1235 | |
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| 0.5382 | 19.0 | 3686 | 1.6114 | 4.7385 | 75.4196 | |
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| 0.5382 | 20.0 | 3880 | 1.6214 | 5.2447 | 75.7202 | |
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| 0.5134 | 21.0 | 4074 | 1.6299 | 5.2439 | 76.8512 | |
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| 0.5134 | 22.0 | 4268 | 1.6349 | 4.9998 | 74.7768 | |
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| 0.5134 | 23.0 | 4462 | 1.6441 | 5.1979 | 74.4405 | |
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| 0.4938 | 24.0 | 4656 | 1.6538 | 4.9686 | 74.8661 | |
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| 0.4938 | 25.0 | 4850 | 1.6586 | 5.2127 | 75.1042 | |
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| 0.4737 | 26.0 | 5044 | 1.6603 | 5.1942 | 75.1562 | |
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| 0.4737 | 27.0 | 5238 | 1.6760 | 5.218 | 75.4524 | |
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| 0.4737 | 28.0 | 5432 | 1.6764 | 4.9681 | 74.9092 | |
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| 0.4536 | 29.0 | 5626 | 1.6822 | 4.8603 | 75.442 | |
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| 0.4536 | 30.0 | 5820 | 1.6905 | 5.1553 | 75.9107 | |
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| 0.4358 | 31.0 | 6014 | 1.7020 | 4.9345 | 75.0193 | |
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| 0.4358 | 32.0 | 6208 | 1.7056 | 5.2455 | 75.3586 | |
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| 0.4358 | 33.0 | 6402 | 1.7083 | 5.083 | 76.5923 | |
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| 0.4184 | 34.0 | 6596 | 1.7148 | 5.0844 | 75.9792 | |
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| 0.4184 | 35.0 | 6790 | 1.7255 | 5.6166 | 76.0952 | |
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| 0.4184 | 36.0 | 6984 | 1.7198 | 5.1109 | 74.119 | |
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| 0.4041 | 37.0 | 7178 | 1.7409 | 5.1895 | 75.317 | |
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| 0.4041 | 38.0 | 7372 | 1.7467 | 5.1409 | 76.192 | |
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| 0.3871 | 39.0 | 7566 | 1.7457 | 5.2776 | 76.1384 | |
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| 0.3871 | 40.0 | 7760 | 1.7566 | 5.1878 | 76.5744 | |
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| 0.3871 | 41.0 | 7954 | 1.7648 | 5.1553 | 76.7202 | |
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| 0.3715 | 42.0 | 8148 | 1.7644 | 5.3827 | 75.1235 | |
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| 0.3715 | 43.0 | 8342 | 1.7789 | 4.9848 | 77.0938 | |
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| 0.3588 | 44.0 | 8536 | 1.7774 | 5.3408 | 76.4807 | |
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| 0.3588 | 45.0 | 8730 | 1.7877 | 5.2917 | 75.7098 | |
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| 0.3588 | 46.0 | 8924 | 1.7890 | 5.3424 | 76.5149 | |
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| 0.3461 | 47.0 | 9118 | 1.7962 | 5.2892 | 75.4048 | |
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| 0.3461 | 48.0 | 9312 | 1.8005 | 5.1806 | 76.1235 | |
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| 0.3361 | 49.0 | 9506 | 1.8067 | 5.1191 | 76.2098 | |
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| 0.3361 | 50.0 | 9700 | 1.8131 | 5.4998 | 75.3958 | |
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| 0.3361 | 51.0 | 9894 | 1.8203 | 5.1396 | 76.4926 | |
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| 0.323 | 52.0 | 10088 | 1.8254 | 5.3301 | 76.128 | |
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| 0.323 | 53.0 | 10282 | 1.8288 | 5.1309 | 75.4732 | |
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| 0.323 | 54.0 | 10476 | 1.8355 | 5.067 | 75.3929 | |
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| 0.3145 | 55.0 | 10670 | 1.8387 | 5.0625 | 75.4554 | |
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| 0.3145 | 56.0 | 10864 | 1.8485 | 5.0427 | 76.6399 | |
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| 0.3045 | 57.0 | 11058 | 1.8515 | 5.077 | 75.5685 | |
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| 0.3045 | 58.0 | 11252 | 1.8548 | 5.2864 | 75.5491 | |
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| 0.3045 | 59.0 | 11446 | 1.8647 | 5.1937 | 75.625 | |
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| 0.2954 | 60.0 | 11640 | 1.8638 | 5.2397 | 76.0089 | |
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| 0.2954 | 61.0 | 11834 | 1.8738 | 5.3512 | 75.9628 | |
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| 0.2867 | 62.0 | 12028 | 1.8767 | 5.3713 | 76.4241 | |
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| 0.2867 | 63.0 | 12222 | 1.8765 | 5.5181 | 76.7738 | |
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| 0.2867 | 64.0 | 12416 | 1.8841 | 5.0943 | 76.2932 | |
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| 0.2783 | 65.0 | 12610 | 1.8821 | 4.9868 | 75.7009 | |
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| 0.2783 | 66.0 | 12804 | 1.8915 | 5.4204 | 75.4688 | |
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| 0.2783 | 67.0 | 12998 | 1.8920 | 5.3434 | 75.5952 | |
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| 0.2738 | 68.0 | 13192 | 1.8941 | 5.2259 | 75.5476 | |
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| 0.2738 | 69.0 | 13386 | 1.8997 | 5.4174 | 77.5372 | |
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| 0.2661 | 70.0 | 13580 | 1.9044 | 5.2945 | 76.0312 | |
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| 0.2661 | 71.0 | 13774 | 1.9042 | 5.3489 | 75.7798 | |
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| 0.2661 | 72.0 | 13968 | 1.9087 | 5.1653 | 76.2366 | |
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| 0.2613 | 73.0 | 14162 | 1.9144 | 5.16 | 75.0402 | |
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| 0.2613 | 74.0 | 14356 | 1.9124 | 5.3944 | 74.8854 | |
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| 0.2548 | 75.0 | 14550 | 1.9194 | 4.9676 | 76.2827 | |
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| 0.2548 | 76.0 | 14744 | 1.9208 | 5.3381 | 75.6548 | |
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| 0.2548 | 77.0 | 14938 | 1.9228 | 5.3926 | 76.2024 | |
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| 0.2502 | 78.0 | 15132 | 1.9288 | 5.3713 | 76.0179 | |
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| 0.2502 | 79.0 | 15326 | 1.9292 | 5.3918 | 75.6786 | |
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| 0.2456 | 80.0 | 15520 | 1.9312 | 5.2898 | 76.0179 | |
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| 0.2456 | 81.0 | 15714 | 1.9323 | 5.1955 | 76.3051 | |
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| 0.2456 | 82.0 | 15908 | 1.9350 | 5.1054 | 76.0119 | |
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| 0.242 | 83.0 | 16102 | 1.9393 | 5.2818 | 75.0461 | |
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| 0.242 | 84.0 | 16296 | 1.9402 | 5.3891 | 76.0476 | |
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| 0.242 | 85.0 | 16490 | 1.9410 | 5.0327 | 76.4717 | |
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| 0.2385 | 86.0 | 16684 | 1.9445 | 5.2409 | 77.2262 | |
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| 0.2385 | 87.0 | 16878 | 1.9425 | 5.4225 | 75.7827 | |
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| 0.2341 | 88.0 | 17072 | 1.9485 | 5.2054 | 76.7262 | |
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| 0.2341 | 89.0 | 17266 | 1.9484 | 5.1336 | 75.5818 | |
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| 0.2341 | 90.0 | 17460 | 1.9518 | 5.1384 | 76.0476 | |
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| 0.2327 | 91.0 | 17654 | 1.9516 | 5.2578 | 75.8259 | |
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| 0.2327 | 92.0 | 17848 | 1.9534 | 5.4452 | 76.0655 | |
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| 0.2297 | 93.0 | 18042 | 1.9525 | 5.3555 | 76.5342 | |
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| 0.2297 | 94.0 | 18236 | 1.9533 | 5.3192 | 76.2619 | |
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| 0.2297 | 95.0 | 18430 | 1.9551 | 5.419 | 75.8988 | |
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| 0.2271 | 96.0 | 18624 | 1.9560 | 5.19 | 76.8036 | |
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| 0.2271 | 97.0 | 18818 | 1.9562 | 5.1571 | 76.186 | |
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| 0.226 | 98.0 | 19012 | 1.9570 | 5.1179 | 76.2812 | |
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| 0.226 | 99.0 | 19206 | 1.9575 | 5.2191 | 76.0699 | |
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| 0.226 | 100.0 | 19400 | 1.9576 | 5.2917 | 76.1652 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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