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yesj1234
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ko-en_mbartLarge_exp5p

Text2Text Generation
Transformers
PyTorch
Korean
English
mbart
Generated from Trainer
Inference Endpoints
Model card Files Community
1
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  1. .gitattributes +2 -0
  2. README.md +84 -0
  3. added_tokens.json +59 -0
  4. all_results.json +22 -0
  5. checkpoint-12000/added_tokens.json +59 -0
  6. checkpoint-12000/config.json +59 -0
  7. checkpoint-12000/generation_config.json +12 -0
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  21. config.json +59 -0
  22. eval_results.json +10 -0
  23. generated_predictions.txt +0 -0
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  25. predict_results.json +9 -0
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  27. sentencepiece.bpe.model +3 -0
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  29. tokenizer.json +3 -0
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  31. train_results.json +8 -0
  32. trainer_state.json +380 -0
  33. training_args.bin +3 -0
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README.md ADDED
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+ ---
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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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+
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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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+
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+ # ko-en_mbartLarge_exp5p
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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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