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marian-finetuned-tgl-eng-netspeak-trial9
This model is a fine-tuned version of Helsinki-NLP/opus-mt-tl-en on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.3568
- Bleu: 29.1370
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: 200
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|---|---|---|---|---|
| 5.6316 | 1.0 | 57 | 4.1183 | 4.6005 |
| 4.8654 | 2.0 | 114 | 3.8581 | 5.9435 |
| 4.5642 | 3.0 | 171 | 3.6865 | 6.6312 |
| 4.3364 | 4.0 | 228 | 3.5646 | 7.3157 |
| 4.1474 | 5.0 | 285 | 3.4686 | 8.6700 |
| 4.0044 | 6.0 | 342 | 3.3852 | 8.6733 |
| 3.8862 | 7.0 | 399 | 3.3257 | 8.3894 |
| 3.7676 | 8.0 | 456 | 3.2528 | 9.2599 |
| 3.6633 | 9.0 | 513 | 3.2005 | 9.7922 |
| 3.5594 | 10.0 | 570 | 3.1615 | 10.9836 |
| 3.4683 | 11.0 | 627 | 3.1055 | 11.0111 |
| 3.3897 | 12.0 | 684 | 3.0527 | 11.0658 |
| 3.3165 | 13.0 | 741 | 3.0106 | 11.3570 |
| 3.2338 | 14.0 | 798 | 2.9819 | 12.4296 |
| 3.1626 | 15.0 | 855 | 2.9395 | 13.0279 |
| 3.1127 | 16.0 | 912 | 2.9088 | 13.2959 |
| 3.0224 | 17.0 | 969 | 2.8760 | 13.9185 |
| 2.9523 | 18.0 | 1026 | 2.8420 | 14.7849 |
| 2.9036 | 19.0 | 1083 | 2.8059 | 15.3255 |
| 2.8449 | 20.0 | 1140 | 2.7830 | 15.8899 |
| 2.7851 | 21.0 | 1197 | 2.7654 | 15.3016 |
| 2.7182 | 22.0 | 1254 | 2.7422 | 15.9169 |
| 2.683 | 23.0 | 1311 | 2.7171 | 15.4695 |
| 2.6016 | 24.0 | 1368 | 2.6860 | 17.2504 |
| 2.5688 | 25.0 | 1425 | 2.6800 | 17.4693 |
| 2.511 | 26.0 | 1482 | 2.6523 | 17.8363 |
| 2.4627 | 27.0 | 1539 | 2.6247 | 18.6818 |
| 2.4259 | 28.0 | 1596 | 2.6038 | 19.2026 |
| 2.3814 | 29.0 | 1653 | 2.5946 | 18.9046 |
| 2.3368 | 30.0 | 1710 | 2.5720 | 19.6498 |
| 2.2639 | 31.0 | 1767 | 2.5564 | 18.7972 |
| 2.2366 | 32.0 | 1824 | 2.5432 | 20.1555 |
| 2.1884 | 33.0 | 1881 | 2.5369 | 19.9048 |
| 2.143 | 34.0 | 1938 | 2.5215 | 19.3706 |
| 2.122 | 35.0 | 1995 | 2.5102 | 20.2954 |
| 2.0819 | 36.0 | 2052 | 2.4966 | 20.5785 |
| 2.0333 | 37.0 | 2109 | 2.4939 | 20.8078 |
| 1.9972 | 38.0 | 2166 | 2.4852 | 21.6624 |
| 1.9596 | 39.0 | 2223 | 2.4724 | 21.3380 |
| 1.9386 | 40.0 | 2280 | 2.4550 | 21.7399 |
| 1.8881 | 41.0 | 2337 | 2.4539 | 21.8201 |
| 1.8488 | 42.0 | 2394 | 2.4494 | 22.8561 |
| 1.8344 | 43.0 | 2451 | 2.4436 | 22.0001 |
| 1.8005 | 44.0 | 2508 | 2.4353 | 21.5060 |
| 1.7703 | 45.0 | 2565 | 2.4314 | 22.6523 |
| 1.7321 | 46.0 | 2622 | 2.4258 | 22.9500 |
| 1.6897 | 47.0 | 2679 | 2.4202 | 23.0767 |
| 1.6822 | 48.0 | 2736 | 2.4115 | 23.3565 |
| 1.6392 | 49.0 | 2793 | 2.4056 | 24.4669 |
| 1.621 | 50.0 | 2850 | 2.4071 | 25.7900 |
| 1.6075 | 51.0 | 2907 | 2.3930 | 25.8570 |
| 1.5558 | 52.0 | 2964 | 2.3835 | 26.0207 |
| 1.5335 | 53.0 | 3021 | 2.3848 | 24.5089 |
| 1.5091 | 54.0 | 3078 | 2.3870 | 26.7579 |
| 1.4904 | 55.0 | 3135 | 2.3791 | 26.2250 |
| 1.4645 | 56.0 | 3192 | 2.3760 | 26.1819 |
| 1.4628 | 57.0 | 3249 | 2.3811 | 25.9747 |
| 1.4297 | 58.0 | 3306 | 2.3659 | 26.4407 |
| 1.4011 | 59.0 | 3363 | 2.3650 | 27.1145 |
| 1.3649 | 60.0 | 3420 | 2.3597 | 27.6616 |
| 1.3419 | 61.0 | 3477 | 2.3601 | 28.6248 |
| 1.3278 | 62.0 | 3534 | 2.3670 | 27.2075 |
| 1.3106 | 63.0 | 3591 | 2.3588 | 27.3917 |
| 1.2855 | 64.0 | 3648 | 2.3508 | 27.8277 |
| 1.2732 | 65.0 | 3705 | 2.3622 | 28.3032 |
| 1.259 | 66.0 | 3762 | 2.3603 | 28.0315 |
| 1.2397 | 67.0 | 3819 | 2.3551 | 27.9452 |
| 1.2285 | 68.0 | 3876 | 2.3597 | 28.5887 |
| 1.1898 | 69.0 | 3933 | 2.3599 | 28.5675 |
| 1.181 | 70.0 | 3990 | 2.3642 | 29.7412 |
| 1.1748 | 71.0 | 4047 | 2.3577 | 29.2003 |
| 1.146 | 72.0 | 4104 | 2.3609 | 28.3760 |
| 1.1274 | 73.0 | 4161 | 2.3519 | 29.2015 |
| 1.1138 | 74.0 | 4218 | 2.3568 | 29.1370 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
