combined_marianmt_sanlish_to_bangla_epoch25
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: 1.6589
- Bleu: 10.9934
- Chrf: 38.8597
- Meteor: 0.3027
- Bertscore F1: 0.8431
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: 25
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Chrf | Meteor | Bertscore F1 |
|---|---|---|---|---|---|---|---|
| 3.4867 | 1.0 | 246 | 2.4953 | 0.3013 | 11.3201 | 0.0297 | 0.725 |
| 2.4133 | 2.0 | 492 | 2.1473 | 0.6426 | 13.563 | 0.0506 | 0.749 |
| 2.0753 | 3.0 | 738 | 1.9103 | 1.921 | 19.4409 | 0.1044 | 0.777 |
| 1.7616 | 4.0 | 984 | 1.7607 | 3.6539 | 23.9 | 0.142 | 0.7939 |
| 1.5058 | 5.0 | 1230 | 1.6992 | 3.4247 | 27.293 | 0.1882 | 0.8078 |
| 1.3095 | 6.0 | 1476 | 1.6391 | 4.6868 | 29.0131 | 0.204 | 0.815 |
| 1.1616 | 7.0 | 1722 | 1.5981 | 6.5137 | 31.0419 | 0.2256 | 0.821 |
| 1.0289 | 8.0 | 1968 | 1.5805 | 7.1741 | 33.3236 | 0.2333 | 0.8257 |
| 0.9136 | 9.0 | 2214 | 1.5644 | 10.2041 | 34.4361 | 0.2499 | 0.8311 |
| 0.8246 | 10.0 | 2460 | 1.5826 | 9.4203 | 34.8978 | 0.2498 | 0.8303 |
| 0.7421 | 11.0 | 2706 | 1.5625 | 8.6133 | 35.331 | 0.2567 | 0.8326 |
| 0.6666 | 12.0 | 2952 | 1.5989 | 7.9675 | 35.9283 | 0.2655 | 0.8345 |
| 0.605 | 13.0 | 3198 | 1.5774 | 8.5414 | 36.5257 | 0.2707 | 0.8344 |
| 0.5581 | 14.0 | 3444 | 1.5885 | 9.8217 | 37.8949 | 0.2779 | 0.8389 |
| 0.5159 | 15.0 | 3690 | 1.6101 | 10.3227 | 37.5904 | 0.2828 | 0.8384 |
| 0.4817 | 16.0 | 3936 | 1.6000 | 11.1169 | 38.2473 | 0.2918 | 0.8404 |
| 0.4378 | 17.0 | 4182 | 1.6189 | 10.0945 | 38.8729 | 0.2903 | 0.8441 |
| 0.4151 | 18.0 | 4428 | 1.6312 | 9.92 | 38.5636 | 0.2941 | 0.8411 |
| 0.3888 | 19.0 | 4674 | 1.6346 | 10.4983 | 38.6156 | 0.2991 | 0.8426 |
| 0.3645 | 20.0 | 4920 | 1.6442 | 10.5683 | 38.9307 | 0.3012 | 0.8443 |
| 0.3447 | 21.0 | 5166 | 1.6457 | 10.4767 | 38.8105 | 0.3043 | 0.8436 |
| 0.3277 | 22.0 | 5412 | 1.6523 | 11.544 | 39.756 | 0.3081 | 0.8453 |
| 0.3227 | 23.0 | 5658 | 1.6586 | 11.0236 | 38.6142 | 0.2986 | 0.8427 |
| 0.3095 | 24.0 | 5904 | 1.6593 | 11.0408 | 38.7821 | 0.3002 | 0.8426 |
| 0.3072 | 25.0 | 6150 | 1.6589 | 10.9934 | 38.8597 | 0.3027 | 0.8431 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.11.0+cu128
- Datasets 4.8.5
- Tokenizers 0.20.3