marianmt-santali-ipa-to-bangla_normalSplit
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-mul on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7438
- Bleu: 10.8230
- Chrf: 35.9474
- Meteor: 0.3051
- Bertscore: 0.8376
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Chrf | Meteor | Bertscore |
|---|---|---|---|---|---|---|---|
| 2.8745 | 1.0 | 194 | 2.5988 | 0.3358 | 10.8306 | 0.0336 | 0.7126 |
| 2.5044 | 2.0 | 388 | 2.2998 | 0.5050 | 12.3618 | 0.0469 | 0.7310 |
| 2.2231 | 3.0 | 582 | 2.1207 | 1.4073 | 15.1310 | 0.0825 | 0.7558 |
| 2.024 | 4.0 | 776 | 1.9867 | 2.1319 | 18.0802 | 0.1291 | 0.7761 |
| 1.7752 | 5.0 | 970 | 1.8718 | 2.5581 | 22.2991 | 0.1773 | 0.7907 |
| 1.4984 | 6.0 | 1164 | 1.7765 | 3.4326 | 25.0497 | 0.2008 | 0.7978 |
| 1.3704 | 7.0 | 1358 | 1.7767 | 3.3985 | 25.0114 | 0.2034 | 0.7984 |
| 1.2993 | 8.0 | 1552 | 1.7245 | 5.3114 | 25.9564 | 0.2172 | 0.8083 |
| 1.1183 | 9.0 | 1746 | 1.7270 | 4.9278 | 27.5015 | 0.2295 | 0.8131 |
| 1.116 | 10.0 | 1940 | 1.6764 | 7.0247 | 29.4231 | 0.2548 | 0.8206 |
| 0.9505 | 11.0 | 2134 | 1.6977 | 5.7992 | 30.0031 | 0.2531 | 0.8200 |
| 0.8805 | 12.0 | 2328 | 1.6682 | 7.0811 | 31.1998 | 0.2605 | 0.8226 |
| 0.7953 | 13.0 | 2522 | 1.6678 | 7.1778 | 32.4209 | 0.2786 | 0.8301 |
| 0.7558 | 14.0 | 2716 | 1.6792 | 6.8708 | 32.6178 | 0.2809 | 0.8298 |
| 0.7147 | 15.0 | 2910 | 1.6694 | 8.7661 | 33.8030 | 0.2923 | 0.8311 |
| 0.6098 | 16.0 | 3104 | 1.6749 | 8.2144 | 34.1549 | 0.2960 | 0.8363 |
| 0.6088 | 17.0 | 3298 | 1.6897 | 8.8893 | 33.5770 | 0.2940 | 0.8359 |
| 0.5913 | 18.0 | 3492 | 1.6957 | 8.9283 | 33.5152 | 0.2961 | 0.8318 |
| 0.5362 | 19.0 | 3686 | 1.6878 | 9.1546 | 33.9310 | 0.2973 | 0.8342 |
| 0.4918 | 20.0 | 3880 | 1.7068 | 9.4396 | 35.3776 | 0.3056 | 0.8357 |
| 0.4642 | 21.0 | 4074 | 1.6999 | 10.2171 | 35.5317 | 0.3062 | 0.8399 |
| 0.4272 | 22.0 | 4268 | 1.7180 | 9.9976 | 35.1329 | 0.3048 | 0.8360 |
| 0.4119 | 23.0 | 4462 | 1.7229 | 10.3259 | 35.4247 | 0.3050 | 0.8373 |
| 0.3877 | 24.0 | 4656 | 1.7212 | 10.5739 | 35.4685 | 0.3052 | 0.8356 |
| 0.3964 | 25.0 | 4850 | 1.7379 | 10.3918 | 36.3235 | 0.3105 | 0.8397 |
| 0.3571 | 26.0 | 5044 | 1.7341 | 10.9371 | 36.3835 | 0.3137 | 0.8413 |
| 0.3462 | 27.0 | 5238 | 1.7381 | 10.5170 | 35.7879 | 0.3105 | 0.8378 |
| 0.3184 | 28.0 | 5432 | 1.7400 | 10.5324 | 35.6082 | 0.3129 | 0.8391 |
| 0.354 | 29.0 | 5626 | 1.7422 | 11.3840 | 36.3976 | 0.3079 | 0.8379 |
| 0.3315 | 30.0 | 5820 | 1.7438 | 10.8230 | 35.9474 | 0.3051 | 0.8376 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.20.3