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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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- open_subtitles |
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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-open-subtitles |
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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: open_subtitles |
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type: open_subtitles |
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config: en-id |
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split: train |
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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: 30.2272 |
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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-open-subtitles |
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This model was trained from scratch on the open_subtitles dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3148 |
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- Bleu: 30.2272 |
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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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| 1.5356 | 1.0 | 28125 | 1.5619 | 31.8599 | |
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| 1.4703 | 2.0 | 56250 | 1.6047 | 31.8339 | |
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| 1.3857 | 3.0 | 84375 | 1.6281 | 32.0796 | |
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| 1.313 | 4.0 | 112500 | 1.6619 | 31.7391 | |
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| 1.2468 | 5.0 | 140625 | 1.6706 | 31.9009 | |
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| 1.1831 | 6.0 | 168750 | 1.6924 | 31.4491 | |
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| 1.1232 | 7.0 | 196875 | 1.7252 | 31.7229 | |
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| 1.0649 | 8.0 | 225000 | 1.7483 | 31.7093 | |
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| 1.0078 | 9.0 | 253125 | 1.7697 | 31.4902 | |
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| 0.9516 | 10.0 | 281250 | 1.8026 | 31.4342 | |
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| 0.8969 | 11.0 | 309375 | 1.8364 | 31.2466 | |
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| 0.8436 | 12.0 | 337500 | 1.8747 | 31.1737 | |
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| 0.7916 | 13.0 | 365625 | 1.9035 | 31.0118 | |
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| 0.7406 | 14.0 | 393750 | 1.9414 | 30.9409 | |
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| 0.6912 | 15.0 | 421875 | 1.9776 | 30.9562 | |
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| 0.6439 | 16.0 | 450000 | 2.0221 | 30.582 | |
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| 0.5983 | 17.0 | 478125 | 2.0588 | 30.4478 | |
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| 0.5544 | 18.0 | 506250 | 2.1023 | 30.4601 | |
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| 0.5126 | 19.0 | 534375 | 2.1367 | 30.4802 | |
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| 0.474 | 20.0 | 562500 | 2.1790 | 30.4211 | |
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| 0.438 | 21.0 | 590625 | 2.2131 | 30.3327 | |
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| 0.4039 | 22.0 | 618750 | 2.2484 | 30.196 | |
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| 0.3737 | 23.0 | 646875 | 2.2779 | 30.1145 | |
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| 0.3475 | 24.0 | 675000 | 2.3022 | 30.2635 | |
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| 0.326 | 25.0 | 703125 | 2.3148 | 30.2272 | |
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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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