--- license: apache-2.0 base_model: Helsinki-NLP/opus-mt-en-es tags: - generated_from_trainer metrics: - bleu model-index: - name: opus-mt-en-es-finetuned-es-to-maq-v2 results: [] --- # opus-mt-en-es-finetuned-es-to-maq-v2 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. It achieves the following results on the evaluation set: - Loss: 1.5183 - Bleu: 14.1223 - Gen Len: 80.4685 ## 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: 2e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |:-------------:|:-----:|:-----:|:---------------:|:-------:|:--------:| | No log | 1.0 | 199 | 2.3315 | 2.9691 | 112.5882 | | No log | 2.0 | 398 | 2.0603 | 4.7361 | 89.3715 | | 2.622 | 3.0 | 597 | 1.9177 | 5.7259 | 93.194 | | 2.622 | 4.0 | 796 | 1.8330 | 6.3357 | 91.4358 | | 2.622 | 5.0 | 995 | 1.7688 | 6.6048 | 89.8879 | | 1.912 | 6.0 | 1194 | 1.7188 | 7.3799 | 89.4118 | | 1.912 | 7.0 | 1393 | 1.6763 | 8.1149 | 86.6839 | | 1.7194 | 8.0 | 1592 | 1.6432 | 8.1903 | 88.4181 | | 1.7194 | 9.0 | 1791 | 1.6160 | 9.0788 | 86.8917 | | 1.7194 | 10.0 | 1990 | 1.5882 | 8.9414 | 87.0982 | | 1.5981 | 11.0 | 2189 | 1.5700 | 9.7369 | 83.1587 | | 1.5981 | 12.0 | 2388 | 1.5505 | 10.2715 | 83.0416 | | 1.5 | 13.0 | 2587 | 1.5264 | 10.1412 | 85.67 | | 1.5 | 14.0 | 2786 | 1.5210 | 10.4181 | 83.9295 | | 1.5 | 15.0 | 2985 | 1.5065 | 10.7716 | 84.1209 | | 1.425 | 16.0 | 3184 | 1.4937 | 11.5064 | 83.8035 | | 1.425 | 17.0 | 3383 | 1.4864 | 11.4935 | 81.8463 | | 1.3564 | 18.0 | 3582 | 1.4735 | 11.5941 | 81.5327 | | 1.3564 | 19.0 | 3781 | 1.4645 | 11.7988 | 81.6562 | | 1.3564 | 20.0 | 3980 | 1.4559 | 12.0264 | 81.8715 | | 1.2981 | 21.0 | 4179 | 1.4518 | 12.2891 | 82.7179 | | 1.2981 | 22.0 | 4378 | 1.4465 | 12.5085 | 80.0101 | | 1.2462 | 23.0 | 4577 | 1.4403 | 12.5034 | 79.8665 | | 1.2462 | 24.0 | 4776 | 1.4347 | 12.6431 | 78.9484 | | 1.2462 | 25.0 | 4975 | 1.4365 | 12.6659 | 80.5214 | | 1.2008 | 26.0 | 5174 | 1.4372 | 13.0592 | 80.8086 | | 1.2008 | 27.0 | 5373 | 1.4306 | 12.4894 | 80.0932 | | 1.1552 | 28.0 | 5572 | 1.4261 | 12.9738 | 80.034 | | 1.1552 | 29.0 | 5771 | 1.4248 | 13.2419 | 79.8199 | | 1.1552 | 30.0 | 5970 | 1.4239 | 13.1865 | 79.5869 | | 1.1184 | 31.0 | 6169 | 1.4229 | 13.3942 | 80.8073 | | 1.1184 | 32.0 | 6368 | 1.4228 | 13.5008 | 79.762 | | 1.0828 | 33.0 | 6567 | 1.4211 | 13.7336 | 79.3086 | | 1.0828 | 34.0 | 6766 | 1.4216 | 13.6096 | 80.738 | | 1.0828 | 35.0 | 6965 | 1.4206 | 13.3387 | 81.9622 | | 1.0484 | 36.0 | 7164 | 1.4226 | 13.627 | 80.6549 | | 1.0484 | 37.0 | 7363 | 1.4214 | 13.314 | 79.5013 | | 1.0159 | 38.0 | 7562 | 1.4214 | 13.6822 | 80.3212 | | 1.0159 | 39.0 | 7761 | 1.4218 | 13.9024 | 80.573 | | 1.0159 | 40.0 | 7960 | 1.4284 | 13.7823 | 80.694 | | 0.9879 | 41.0 | 8159 | 1.4281 | 13.8635 | 80.8728 | | 0.9879 | 42.0 | 8358 | 1.4292 | 14.0735 | 80.0365 | | 0.9599 | 43.0 | 8557 | 1.4246 | 14.2843 | 80.3766 | | 0.9599 | 44.0 | 8756 | 1.4349 | 14.0705 | 80.0013 | | 0.9599 | 45.0 | 8955 | 1.4324 | 14.2379 | 80.8627 | | 0.9345 | 46.0 | 9154 | 1.4345 | 14.1261 | 80.1146 | | 0.9345 | 47.0 | 9353 | 1.4371 | 13.8716 | 80.5743 | | 0.9099 | 48.0 | 9552 | 1.4387 | 13.8032 | 81.8564 | | 0.9099 | 49.0 | 9751 | 1.4343 | 14.2119 | 81.1675 | | 0.9099 | 50.0 | 9950 | 1.4400 | 13.9887 | 80.4106 | | 0.8875 | 51.0 | 10149 | 1.4394 | 14.2409 | 81.335 | | 0.8875 | 52.0 | 10348 | 1.4451 | 14.1096 | 81.0189 | | 0.8663 | 53.0 | 10547 | 1.4486 | 14.2637 | 80.4509 | | 0.8663 | 54.0 | 10746 | 1.4514 | 14.079 | 79.9786 | | 0.8663 | 55.0 | 10945 | 1.4503 | 14.0559 | 80.4307 | | 0.8472 | 56.0 | 11144 | 1.4537 | 14.2922 | 80.4534 | | 0.8472 | 57.0 | 11343 | 1.4560 | 14.5289 | 80.4496 | | 0.828 | 58.0 | 11542 | 1.4574 | 14.1122 | 80.1826 | | 0.828 | 59.0 | 11741 | 1.4592 | 13.9756 | 80.5592 | | 0.828 | 60.0 | 11940 | 1.4639 | 13.9926 | 81.9547 | | 0.8091 | 61.0 | 12139 | 1.4650 | 14.1126 | 80.097 | | 0.8091 | 62.0 | 12338 | 1.4639 | 14.1419 | 80.3929 | | 0.7937 | 63.0 | 12537 | 1.4722 | 14.2943 | 80.8073 | | 0.7937 | 64.0 | 12736 | 1.4680 | 13.8719 | 81.3753 | | 0.7937 | 65.0 | 12935 | 1.4764 | 14.1477 | 80.903 | | 0.7798 | 66.0 | 13134 | 1.4776 | 14.239 | 80.8312 | | 0.7798 | 67.0 | 13333 | 1.4759 | 14.1653 | 80.3866 | | 0.7657 | 68.0 | 13532 | 1.4796 | 14.092 | 80.1763 | | 0.7657 | 69.0 | 13731 | 1.4814 | 14.2321 | 80.9433 | | 0.7657 | 70.0 | 13930 | 1.4814 | 14.1632 | 80.5957 | | 0.7514 | 71.0 | 14129 | 1.4850 | 14.0296 | 81.2217 | | 0.7514 | 72.0 | 14328 | 1.4878 | 14.2263 | 80.6751 | | 0.7407 | 73.0 | 14527 | 1.4896 | 13.962 | 81.4572 | | 0.7407 | 74.0 | 14726 | 1.4920 | 14.225 | 81.1788 | | 0.7407 | 75.0 | 14925 | 1.4923 | 13.9021 | 81.0176 | | 0.7297 | 76.0 | 15124 | 1.4956 | 13.8359 | 80.8539 | | 0.7297 | 77.0 | 15323 | 1.4972 | 14.1418 | 80.9295 | | 0.7198 | 78.0 | 15522 | 1.4992 | 13.8721 | 81.0126 | | 0.7198 | 79.0 | 15721 | 1.5024 | 14.0958 | 81.1788 | | 0.7198 | 80.0 | 15920 | 1.4995 | 14.2018 | 80.4786 | | 0.7099 | 81.0 | 16119 | 1.5032 | 14.074 | 80.8766 | | 0.7099 | 82.0 | 16318 | 1.5060 | 14.301 | 79.6335 | | 0.7042 | 83.0 | 16517 | 1.5047 | 14.0572 | 80.3312 | | 0.7042 | 84.0 | 16716 | 1.5061 | 14.19 | 80.0126 | | 0.7042 | 85.0 | 16915 | 1.5088 | 14.2626 | 79.9181 | | 0.6953 | 86.0 | 17114 | 1.5093 | 14.1371 | 80.4924 | | 0.6953 | 87.0 | 17313 | 1.5101 | 13.9727 | 80.6209 | | 0.6897 | 88.0 | 17512 | 1.5096 | 14.088 | 80.1008 | | 0.6897 | 89.0 | 17711 | 1.5137 | 14.117 | 80.5453 | | 0.6897 | 90.0 | 17910 | 1.5143 | 13.9316 | 81.5428 | | 0.6842 | 91.0 | 18109 | 1.5146 | 14.0166 | 80.4207 | | 0.6842 | 92.0 | 18308 | 1.5156 | 14.073 | 80.6625 | | 0.6806 | 93.0 | 18507 | 1.5147 | 14.1289 | 80.2481 | | 0.6806 | 94.0 | 18706 | 1.5148 | 14.143 | 80.301 | | 0.6806 | 95.0 | 18905 | 1.5167 | 13.9649 | 81.0227 | | 0.6765 | 96.0 | 19104 | 1.5179 | 14.1042 | 79.9698 | | 0.6765 | 97.0 | 19303 | 1.5174 | 13.9834 | 80.5793 | | 0.6731 | 98.0 | 19502 | 1.5182 | 14.0637 | 80.5705 | | 0.6731 | 99.0 | 19701 | 1.5183 | 14.0274 | 80.3199 | | 0.6731 | 100.0 | 19900 | 1.5183 | 14.1223 | 80.4685 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3