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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- opus100 |
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metrics: |
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- bleu |
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model-index: |
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- name: opus-mt-en-id-opus100 |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: opus100 |
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type: opus100 |
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config: en-id |
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split: validation |
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args: en-id |
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metrics: |
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- name: Bleu |
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type: bleu |
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value: 27.5354 |
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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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# opus-mt-en-id-opus100 |
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This model was trained from scratch on the opus100 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3682 |
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- Bleu: 27.5354 |
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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: 0.0001 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 4000 |
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- num_epochs: 25 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | |
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|:-------------:|:-----:|:------:|:---------------:|:-------:| |
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| 1.6086 | 1.0 | 31250 | 1.7099 | 29.4293 | |
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| 1.5762 | 2.0 | 62500 | 1.7410 | 28.948 | |
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| 1.5027 | 3.0 | 93750 | 1.7678 | 28.6931 | |
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| 1.4377 | 4.0 | 125000 | 1.7798 | 28.9463 | |
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| 1.3763 | 5.0 | 156250 | 1.8019 | 28.4966 | |
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| 1.3198 | 6.0 | 187500 | 1.8202 | 29.6279 | |
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| 1.2648 | 7.0 | 218750 | 1.8312 | 29.8151 | |
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| 1.2115 | 8.0 | 250000 | 1.8490 | 29.3032 | |
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| 1.1584 | 9.0 | 281250 | 1.8729 | 28.7282 | |
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| 1.1067 | 10.0 | 312500 | 1.8971 | 29.4797 | |
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| 1.0555 | 11.0 | 343750 | 1.9405 | 29.3416 | |
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| 1.0052 | 12.0 | 375000 | 1.9554 | 29.0168 | |
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| 0.956 | 13.0 | 406250 | 2.0001 | 28.2454 | |
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| 0.9069 | 14.0 | 437500 | 2.0282 | 28.6705 | |
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| 0.8589 | 15.0 | 468750 | 2.0591 | 28.1988 | |
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| 0.8115 | 16.0 | 500000 | 2.0944 | 28.2227 | |
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| 0.765 | 17.0 | 531250 | 2.1294 | 28.4351 | |
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| 0.7203 | 18.0 | 562500 | 2.1680 | 27.9764 | |
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| 0.6769 | 19.0 | 593750 | 2.2013 | 28.2986 | |
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| 0.6349 | 20.0 | 625000 | 2.2339 | 27.165 | |
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| 0.5957 | 21.0 | 656250 | 2.2795 | 27.5845 | |
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| 0.5589 | 22.0 | 687500 | 2.3037 | 27.7201 | |
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| 0.5246 | 23.0 | 718750 | 2.3311 | 27.3305 | |
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| 0.4944 | 24.0 | 750000 | 2.3487 | 27.3965 | |
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| 0.469 | 25.0 | 781250 | 2.3682 | 27.5354 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 2.0.0 |
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- Datasets 2.10.1 |
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- Tokenizers 0.11.0 |
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