--- license: apache-2.0 base_model: Helsinki-NLP/opus-mt-en-ar tags: - generated_from_trainer metrics: - bleu model-index: - name: Tounsify-v0.7 results: [] --- # Tounsify-v0.7 This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ar](https://huggingface.co/Helsinki-NLP/opus-mt-en-ar) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.4410 - Bleu: 24.686 - Gen Len: 7.1333 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 100 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:| | No log | 1.0 | 8 | 2.9143 | 16.1913 | 7.4 | | No log | 2.0 | 16 | 2.6238 | 17.5534 | 6.9333 | | No log | 3.0 | 24 | 2.4215 | 11.3684 | 6.3333 | | No log | 4.0 | 32 | 2.2967 | 12.1601 | 6.3 | | No log | 5.0 | 40 | 2.2459 | 12.4837 | 7.0333 | | No log | 6.0 | 48 | 2.2333 | 13.2937 | 6.5667 | | No log | 7.0 | 56 | 2.2264 | 18.1441 | 6.7667 | | No log | 8.0 | 64 | 2.2167 | 14.5825 | 6.5333 | | No log | 9.0 | 72 | 2.2064 | 15.1734 | 6.6667 | | No log | 10.0 | 80 | 2.1951 | 14.6563 | 7.0333 | | No log | 11.0 | 88 | 2.2060 | 19.0714 | 6.6333 | | No log | 12.0 | 96 | 2.2088 | 21.5449 | 6.5333 | | No log | 13.0 | 104 | 2.2517 | 21.4297 | 6.5333 | | No log | 14.0 | 112 | 2.2584 | 24.6131 | 6.6 | | No log | 15.0 | 120 | 2.2411 | 24.7358 | 6.6667 | | No log | 16.0 | 128 | 2.2464 | 24.7358 | 6.6667 | | No log | 17.0 | 136 | 2.2502 | 24.7358 | 6.6667 | | No log | 18.0 | 144 | 2.2567 | 24.7358 | 6.6667 | | No log | 19.0 | 152 | 2.2496 | 24.7358 | 6.6667 | | No log | 20.0 | 160 | 2.2511 | 24.5996 | 6.8 | | No log | 21.0 | 168 | 2.2668 | 24.5996 | 6.8 | | No log | 22.0 | 176 | 2.2805 | 24.7358 | 6.6667 | | No log | 23.0 | 184 | 2.2875 | 24.7358 | 6.6667 | | No log | 24.0 | 192 | 2.2900 | 24.7358 | 6.6667 | | No log | 25.0 | 200 | 2.2828 | 21.51 | 6.6667 | | No log | 26.0 | 208 | 2.2676 | 21.51 | 6.6667 | | No log | 27.0 | 216 | 2.2684 | 24.7358 | 6.6667 | | No log | 28.0 | 224 | 2.2725 | 24.7358 | 6.6667 | | No log | 29.0 | 232 | 2.2768 | 24.7358 | 6.6667 | | No log | 30.0 | 240 | 2.2810 | 24.7358 | 6.6667 | | No log | 31.0 | 248 | 2.2958 | 24.7358 | 6.6667 | | No log | 32.0 | 256 | 2.3036 | 24.7358 | 6.6667 | | No log | 33.0 | 264 | 2.3120 | 24.7358 | 6.7333 | | No log | 34.0 | 272 | 2.3205 | 24.7358 | 6.7333 | | No log | 35.0 | 280 | 2.3305 | 24.7358 | 6.7333 | | No log | 36.0 | 288 | 2.3413 | 24.9721 | 6.7333 | | No log | 37.0 | 296 | 2.3424 | 24.7358 | 6.7333 | | No log | 38.0 | 304 | 2.3472 | 24.7358 | 6.7333 | | No log | 39.0 | 312 | 2.3526 | 24.7358 | 6.7333 | | No log | 40.0 | 320 | 2.3579 | 24.7358 | 6.7333 | | No log | 41.0 | 328 | 2.3630 | 24.7358 | 6.6667 | | No log | 42.0 | 336 | 2.3628 | 24.7358 | 6.6667 | | No log | 43.0 | 344 | 2.3637 | 24.8163 | 6.7667 | | No log | 44.0 | 352 | 2.3619 | 24.8163 | 6.7667 | | No log | 45.0 | 360 | 2.3584 | 24.8163 | 6.7667 | | No log | 46.0 | 368 | 2.3562 | 24.8163 | 6.7667 | | No log | 47.0 | 376 | 2.3605 | 24.8163 | 6.7667 | | No log | 48.0 | 384 | 2.3680 | 24.8163 | 6.8333 | | No log | 49.0 | 392 | 2.3774 | 24.686 | 6.9667 | | No log | 50.0 | 400 | 2.3819 | 24.686 | 6.9667 | | No log | 51.0 | 408 | 2.3850 | 24.686 | 6.9667 | | No log | 52.0 | 416 | 2.3902 | 24.686 | 6.9667 | | No log | 53.0 | 424 | 2.3935 | 24.686 | 6.9667 | | No log | 54.0 | 432 | 2.3969 | 24.686 | 6.9667 | | No log | 55.0 | 440 | 2.3988 | 24.686 | 6.9667 | | No log | 56.0 | 448 | 2.3992 | 24.686 | 6.9667 | | No log | 57.0 | 456 | 2.3986 | 24.686 | 6.9667 | | No log | 58.0 | 464 | 2.3983 | 24.686 | 6.9 | | No log | 59.0 | 472 | 2.4000 | 24.686 | 6.9 | | No log | 60.0 | 480 | 2.4009 | 24.686 | 6.9 | | No log | 61.0 | 488 | 2.4009 | 24.686 | 6.9 | | No log | 62.0 | 496 | 2.4012 | 24.686 | 7.0667 | | 0.2188 | 63.0 | 504 | 2.4027 | 24.686 | 7.0667 | | 0.2188 | 64.0 | 512 | 2.4056 | 24.686 | 7.0667 | | 0.2188 | 65.0 | 520 | 2.4080 | 24.686 | 7.0667 | | 0.2188 | 66.0 | 528 | 2.4085 | 24.686 | 7.0667 | | 0.2188 | 67.0 | 536 | 2.4128 | 24.686 | 7.0667 | | 0.2188 | 68.0 | 544 | 2.4168 | 24.686 | 7.0667 | | 0.2188 | 69.0 | 552 | 2.4201 | 24.686 | 7.0667 | | 0.2188 | 70.0 | 560 | 2.4218 | 24.686 | 6.9 | | 0.2188 | 71.0 | 568 | 2.4229 | 24.686 | 7.0667 | | 0.2188 | 72.0 | 576 | 2.4250 | 24.686 | 7.0667 | | 0.2188 | 73.0 | 584 | 2.4261 | 24.686 | 7.0667 | | 0.2188 | 74.0 | 592 | 2.4262 | 24.686 | 7.0667 | | 0.2188 | 75.0 | 600 | 2.4287 | 24.686 | 7.0667 | | 0.2188 | 76.0 | 608 | 2.4313 | 24.686 | 7.1333 | | 0.2188 | 77.0 | 616 | 2.4294 | 24.686 | 7.1333 | | 0.2188 | 78.0 | 624 | 2.4280 | 24.686 | 7.1333 | | 0.2188 | 79.0 | 632 | 2.4266 | 24.686 | 7.0667 | | 0.2188 | 80.0 | 640 | 2.4257 | 24.686 | 7.0667 | | 0.2188 | 81.0 | 648 | 2.4256 | 24.686 | 7.0667 | | 0.2188 | 82.0 | 656 | 2.4279 | 24.686 | 7.0667 | | 0.2188 | 83.0 | 664 | 2.4312 | 24.686 | 7.0667 | | 0.2188 | 84.0 | 672 | 2.4329 | 24.686 | 7.1333 | | 0.2188 | 85.0 | 680 | 2.4329 | 24.686 | 7.1333 | | 0.2188 | 86.0 | 688 | 2.4324 | 24.686 | 7.1333 | | 0.2188 | 87.0 | 696 | 2.4326 | 24.686 | 7.0667 | | 0.2188 | 88.0 | 704 | 2.4338 | 24.686 | 7.0667 | | 0.2188 | 89.0 | 712 | 2.4343 | 24.686 | 7.0667 | | 0.2188 | 90.0 | 720 | 2.4372 | 24.686 | 7.0667 | | 0.2188 | 91.0 | 728 | 2.4386 | 24.686 | 7.1333 | | 0.2188 | 92.0 | 736 | 2.4396 | 24.686 | 7.1333 | | 0.2188 | 93.0 | 744 | 2.4403 | 24.686 | 7.1333 | | 0.2188 | 94.0 | 752 | 2.4409 | 24.686 | 7.1333 | | 0.2188 | 95.0 | 760 | 2.4416 | 24.686 | 7.1333 | | 0.2188 | 96.0 | 768 | 2.4415 | 24.686 | 7.1333 | | 0.2188 | 97.0 | 776 | 2.4410 | 24.686 | 7.1333 | | 0.2188 | 98.0 | 784 | 2.4411 | 24.686 | 7.1333 | | 0.2188 | 99.0 | 792 | 2.4407 | 24.686 | 7.1333 | | 0.2188 | 100.0 | 800 | 2.4410 | 24.686 | 7.1333 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1