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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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- mt_eng_vietnamese |
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metrics: |
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- bleu |
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model-index: |
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- name: basso4_eng_to_vie_model |
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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: mt_eng_vietnamese |
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type: mt_eng_vietnamese |
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config: iwslt2015-en-vi |
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split: train |
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args: iwslt2015-en-vi |
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metrics: |
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- name: Bleu |
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type: bleu |
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value: 1.3777 |
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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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# basso4_eng_to_vie_model |
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This model was trained from scratch on the mt_eng_vietnamese dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9999 |
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- Bleu: 1.3777 |
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- Gen Len: 18.7953 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:| |
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| 1.3485 | 1.0 | 6666 | 1.2151 | 0.9294 | 18.7893 | |
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| 1.2969 | 2.0 | 13332 | 1.1510 | 1.0593 | 18.7881 | |
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| 1.2426 | 3.0 | 19998 | 1.1053 | 1.1598 | 18.7873 | |
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| 1.2067 | 4.0 | 26664 | 1.0713 | 1.2393 | 18.789 | |
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| 1.1809 | 5.0 | 33330 | 1.0469 | 1.2853 | 18.7894 | |
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| 1.1575 | 6.0 | 39996 | 1.0288 | 1.3227 | 18.7899 | |
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| 1.1407 | 7.0 | 46662 | 1.0154 | 1.3405 | 18.7937 | |
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| 1.1295 | 8.0 | 53328 | 1.0071 | 1.3657 | 18.7943 | |
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| 1.1241 | 9.0 | 59994 | 1.0014 | 1.3753 | 18.7953 | |
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| 1.1209 | 10.0 | 66660 | 0.9999 | 1.3777 | 18.7953 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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