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language: |
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- ko |
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- en |
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base_model: facebook/mbart-large-50-many-to-many-mmt |
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tags: |
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- generated_from_trainer |
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metrics: |
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- bleu |
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model-index: |
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- name: ko-en_mbartLarge_exp5p |
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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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# ko-en_mbartLarge_exp5p |
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This model is a fine-tuned version of [facebook/mbart-large-50-many-to-many-mmt](https://huggingface.co/facebook/mbart-large-50-many-to-many-mmt) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2328 |
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- Bleu: 26.5495 |
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- Gen Len: 18.4213 |
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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: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 40 |
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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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| 1.6447 | 0.46 | 1000 | 1.5338 | 20.0927 | 18.3986 | |
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| 1.4737 | 0.93 | 2000 | 1.4057 | 22.6168 | 18.5462 | |
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| 1.3708 | 1.39 | 3000 | 1.3645 | 23.158 | 18.5132 | |
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| 1.3357 | 1.86 | 4000 | 1.3166 | 24.2178 | 18.4343 | |
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| 1.2274 | 2.32 | 5000 | 1.2854 | 24.8105 | 18.4761 | |
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| 1.2113 | 2.78 | 6000 | 1.2622 | 25.4518 | 18.2672 | |
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| 1.1392 | 3.25 | 7000 | 1.2540 | 25.6184 | 18.4032 | |
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| 1.125 | 3.71 | 8000 | 1.2401 | 25.3848 | 18.3781 | |
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| 1.0423 | 4.18 | 9000 | 1.2354 | 25.9776 | 18.3387 | |
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| 1.011 | 4.64 | 10000 | 1.2418 | 26.1619 | 18.4858 | |
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| 0.9493 | 5.1 | 11000 | 1.2616 | 25.6398 | 18.2273 | |
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| 0.888 | 5.57 | 12000 | 1.2328 | 26.5446 | 18.438 | |
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| 0.8648 | 6.03 | 13000 | 1.2618 | 26.0371 | 18.4074 | |
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| 0.776 | 6.5 | 14000 | 1.2669 | 26.0043 | 18.4629 | |
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| 0.7856 | 6.96 | 15000 | 1.2592 | 26.2716 | 18.403 | |
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| 0.6997 | 7.42 | 16000 | 1.3154 | 25.7842 | 18.3693 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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