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yesj1234
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ko-en_mbartLarge_exp10p

Text2Text Generation
Transformers
PyTorch
Korean
English
mbart
Generated from Trainer
Inference Endpoints
Model card Files Community
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  1. .gitattributes +2 -0
  2. README.md +82 -0
  3. added_tokens.json +59 -0
  4. all_results.json +22 -0
  5. checkpoint-20000/added_tokens.json +59 -0
  6. checkpoint-20000/config.json +59 -0
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  17. checkpoint-20000/tokenizer.json +3 -0
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  19. checkpoint-20000/trainer_state.json +359 -0
  20. checkpoint-20000/training_args.bin +3 -0
  21. config.json +59 -0
  22. eval_results.json +10 -0
  23. generated_predictions.txt +0 -0
  24. generation_config.json +12 -0
  25. predict_results.json +9 -0
  26. pytorch_model.bin +3 -0
  27. sentencepiece.bpe.model +3 -0
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  29. tokenizer.json +3 -0
  30. tokenizer_config.json +528 -0
  31. train_results.json +8 -0
  32. trainer_state.json +504 -0
  33. training_args.bin +3 -0
.gitattributes CHANGED
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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_exp10p
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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_exp10p
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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: 1.1770
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+ - Bleu: 27.7431
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+ - Gen Len: 18.6157
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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_with_restarts
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+ - lr_scheduler_warmup_steps: 1000
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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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+ | 1.5087 | 0.46 | 2000 | 1.4383 | 21.689 | 18.6869 |
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+ | 1.3739 | 0.93 | 4000 | 1.3328 | 23.8363 | 18.7463 |
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+ | 1.2585 | 1.39 | 6000 | 1.2720 | 24.7319 | 18.4624 |
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+ | 1.2355 | 1.86 | 8000 | 1.2356 | 26.1612 | 18.484 |
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+ | 1.0973 | 2.32 | 10000 | 1.2074 | 26.6567 | 18.554 |
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+ | 1.1157 | 2.78 | 12000 | 1.2069 | 26.4733 | 18.8044 |
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+ | 0.9631 | 3.25 | 14000 | 1.1901 | 27.1062 | 18.6803 |
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+ | 1.0223 | 3.71 | 16000 | 1.2280 | 26.3038 | 18.7993 |
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+ | 0.8621 | 4.18 | 18000 | 1.2185 | 26.8035 | 18.6679 |
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+ | 0.866 | 4.64 | 20000 | 1.1770 | 27.7431 | 18.6157 |
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+ | 0.7063 | 5.11 | 22000 | 1.2176 | 27.7268 | 18.6026 |
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+ | 0.7504 | 5.57 | 24000 | 1.2268 | 27.053 | 18.5299 |
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+ | 0.6986 | 6.03 | 26000 | 1.2739 | 27.5119 | 18.7806 |
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+ | 0.6193 | 6.5 | 28000 | 1.2745 | 27.3877 | 18.5109 |
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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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