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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-id-en-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: 36.9382 |
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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-id-en-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: 1.8430 |
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- Bleu: 36.9382 |
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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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| 1.3533 | 1.0 | 28125 | 1.3274 | 37.6662 | |
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| 1.2814 | 2.0 | 56250 | 1.3525 | 37.5909 | |
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| 1.2058 | 3.0 | 84375 | 1.3674 | 37.8008 | |
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| 1.1415 | 4.0 | 112500 | 1.3722 | 37.4849 | |
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| 1.0842 | 5.0 | 140625 | 1.3943 | 37.7558 | |
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| 1.0309 | 6.0 | 168750 | 1.3994 | 37.6332 | |
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| 0.9802 | 7.0 | 196875 | 1.4216 | 37.7529 | |
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| 0.9316 | 8.0 | 225000 | 1.4304 | 37.9906 | |
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| 0.8838 | 9.0 | 253125 | 1.4462 | 37.7833 | |
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| 0.8378 | 10.0 | 281250 | 1.4639 | 37.5971 | |
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| 0.7921 | 11.0 | 309375 | 1.4859 | 37.6285 | |
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| 0.7484 | 12.0 | 337500 | 1.5060 | 37.5413 | |
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| 0.7043 | 13.0 | 365625 | 1.5256 | 37.5118 | |
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| 0.6622 | 14.0 | 393750 | 1.5555 | 37.5092 | |
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| 0.6208 | 15.0 | 421875 | 1.5733 | 37.2924 | |
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| 0.5807 | 16.0 | 450000 | 1.6048 | 37.319 | |
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| 0.542 | 17.0 | 478125 | 1.6435 | 37.0629 | |
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| 0.5043 | 18.0 | 506250 | 1.6647 | 37.1334 | |
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| 0.4685 | 19.0 | 534375 | 1.7014 | 37.02 | |
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| 0.4352 | 20.0 | 562500 | 1.7300 | 36.9514 | |
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| 0.4031 | 21.0 | 590625 | 1.7572 | 36.9637 | |
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| 0.3731 | 22.0 | 618750 | 1.7902 | 36.9821 | |
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| 0.346 | 23.0 | 646875 | 1.8112 | 36.9586 | |
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| 0.3227 | 24.0 | 675000 | 1.8325 | 36.9286 | |
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| 0.303 | 25.0 | 703125 | 1.8430 | 36.9382 | |
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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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