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opus-mt-tr-en-finetuned-tr-to-en
This model is a fine-tuned version of Helsinki-NLP/opus-mt-tr-en on the opus_infopankki dataset. It achieves the following results on the evaluation set:
- Loss: 0.6321
- Bleu: 56.617
- Gen Len: 13.5983
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-06
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| No log | 1.0 | 241 | 1.2487 | 41.0053 | 13.0461 |
| No log | 2.0 | 482 | 1.1630 | 43.1077 | 13.0386 |
| 1.4091 | 3.0 | 723 | 1.0992 | 44.6583 | 13.0445 |
| 1.4091 | 4.0 | 964 | 1.0463 | 45.5931 | 13.0289 |
| 1.2325 | 5.0 | 1205 | 1.0012 | 46.7039 | 12.9998 |
| 1.2325 | 6.0 | 1446 | 0.9610 | 47.6783 | 13.0274 |
| 1.1284 | 7.0 | 1687 | 0.9262 | 48.622 | 12.9866 |
| 1.1284 | 8.0 | 1928 | 0.8939 | 48.4984 | 13.5762 |
| 1.0486 | 9.0 | 2169 | 0.8642 | 49.1496 | 13.5918 |
| 1.0486 | 10.0 | 2410 | 0.8391 | 49.8875 | 13.5905 |
| 0.9866 | 11.0 | 2651 | 0.8150 | 50.6447 | 13.5803 |
| 0.9866 | 12.0 | 2892 | 0.7941 | 51.2059 | 13.5731 |
| 0.9362 | 13.0 | 3133 | 0.7741 | 51.7071 | 13.5754 |
| 0.9362 | 14.0 | 3374 | 0.7564 | 52.4185 | 13.5781 |
| 0.8928 | 15.0 | 3615 | 0.7398 | 53.0814 | 13.5744 |
| 0.8928 | 16.0 | 3856 | 0.7247 | 53.5711 | 13.5783 |
| 0.8598 | 17.0 | 4097 | 0.7111 | 54.0559 | 13.568 |
| 0.8598 | 18.0 | 4338 | 0.6988 | 54.5188 | 13.5598 |
| 0.8274 | 19.0 | 4579 | 0.6876 | 54.78 | 13.5765 |
| 0.8274 | 20.0 | 4820 | 0.6780 | 55.1494 | 13.5762 |
| 0.8086 | 21.0 | 5061 | 0.6688 | 55.5813 | 13.5788 |
| 0.8086 | 22.0 | 5302 | 0.6610 | 55.6403 | 13.5796 |
| 0.7878 | 23.0 | 5543 | 0.6539 | 55.7731 | 13.5989 |
| 0.7878 | 24.0 | 5784 | 0.6483 | 55.9956 | 13.593 |
| 0.7718 | 25.0 | 6025 | 0.6432 | 56.2303 | 13.5904 |
| 0.7718 | 26.0 | 6266 | 0.6390 | 56.4825 | 13.5975 |
| 0.7633 | 27.0 | 6507 | 0.6360 | 56.5334 | 13.5958 |
| 0.7633 | 28.0 | 6748 | 0.6338 | 56.5357 | 13.5965 |
| 0.7633 | 29.0 | 6989 | 0.6325 | 56.5862 | 13.5974 |
| 0.7584 | 30.0 | 7230 | 0.6321 | 56.617 | 13.5983 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.3.2
- Tokenizers 0.12.1
