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--- |
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library_name: transformers |
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language: |
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- nan |
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license: apache-2.0 |
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base_model: Helsinki-NLP/opus-mt-en-ZH |
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tags: |
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- generated_from_trainer |
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datasets: |
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- sarahwei/Taiwanese-Minnan-Example-Sentences |
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metrics: |
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- bleu |
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model-index: |
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- name: helsinki_new_ver5.0 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# helsinki_new_ver5.0 |
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ZH](https://huggingface.co/Helsinki-NLP/opus-mt-en-ZH) on the sarahwei/Taiwanese-Minnan-Example-Sentences dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1331 |
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- Bleu: 24.8564 |
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- Ter: 51.5767 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 8e-06 |
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- train_batch_size: 8 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 1000 |
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- training_steps: 15000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Ter | |
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|:-------------:|:------:|:-----:|:---------------:|:-------:|:-------:| |
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| 0.3275 | 0.5656 | 1000 | 0.2091 | 1.0420 | 80.6027 | |
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| 0.2661 | 1.1312 | 2000 | 0.1750 | 8.8029 | 63.5599 | |
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| 0.2414 | 1.6968 | 3000 | 0.1592 | 14.6322 | 59.3833 | |
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| 0.2165 | 2.2624 | 4000 | 0.1512 | 17.7486 | 55.9776 | |
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| 0.2079 | 2.8281 | 5000 | 0.1457 | 19.9557 | 54.1135 | |
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| 0.1953 | 3.3937 | 6000 | 0.1433 | 21.4108 | 53.4688 | |
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| 0.188 | 3.9593 | 7000 | 0.1410 | 21.9998 | 52.9643 | |
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| 0.1804 | 4.5249 | 8000 | 0.1379 | 22.9829 | 52.6279 | |
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| 0.1797 | 5.0905 | 9000 | 0.1367 | 23.1706 | 52.3196 | |
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| 0.1745 | 5.6561 | 10000 | 0.1355 | 23.3668 | 51.8290 | |
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| 0.1662 | 6.2217 | 11000 | 0.1343 | 24.1466 | 51.7169 | |
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| 0.1691 | 6.7873 | 12000 | 0.1342 | 24.4332 | 51.9972 | |
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| 0.1631 | 7.3529 | 13000 | 0.1335 | 24.4473 | 51.6608 | |
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| 0.1646 | 7.9186 | 14000 | 0.1330 | 24.6473 | 51.6748 | |
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| 0.1599 | 8.4842 | 15000 | 0.1331 | 24.8564 | 51.5767 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.5.1 |
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- Tokenizers 0.21.1 |
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