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yesj1234
/
mbart-mmt_mid1_ko-en

Text2Text Generation
Transformers
PyTorch
Korean
English
mbart
Generated from Trainer
Inference Endpoints
Model card Files Community
yesj1234 commited on
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  1. .gitattributes +2 -0
  2. README.md +79 -0
  3. added_tokens.json +59 -0
  4. all_results.json +22 -0
  5. checkpoint-16000/added_tokens.json +59 -0
  6. checkpoint-16000/config.json +59 -0
  7. checkpoint-16000/generation_config.json +12 -0
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  13. checkpoint-16000/rng_state_3.pth +3 -0
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  17. checkpoint-16000/tokenizer.json +3 -0
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  19. checkpoint-16000/trainer_state.json +291 -0
  20. checkpoint-16000/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
  28. special_tokens_map.json +63 -0
  29. tokenizer.json +3 -0
  30. tokenizer_config.json +528 -0
  31. train_results.json +8 -0
  32. trainer_state.json +436 -0
  33. training_args.bin +3 -0
.gitattributes CHANGED
@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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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: tst-translation-output
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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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+ # tst-translation-output
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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: 1.4429
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+ - Bleu: 21.4825
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+ - Gen Len: 18.792
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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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+ - total_train_batch_size: 16
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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: linear
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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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+ | 1.3784 | 0.23 | 2000 | 1.5514 | 18.2602 | 19.2938 |
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+ | 1.2953 | 0.46 | 4000 | 1.5006 | 19.6277 | 18.7905 |
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+ | 1.2446 | 0.7 | 6000 | 1.4664 | 20.2667 | 19.2503 |
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+ | 1.2095 | 0.93 | 8000 | 1.4482 | 20.8962 | 18.9352 |
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+ | 0.9279 | 1.16 | 10000 | 1.4799 | 20.9876 | 19.093 |
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+ | 0.9604 | 1.39 | 12000 | 1.4672 | 21.261 | 18.8735 |
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+ | 0.9543 | 1.62 | 14000 | 1.4611 | 21.1987 | 18.8396 |
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+ | 0.9532 | 1.86 | 16000 | 1.4429 | 21.4802 | 18.8239 |
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+ | 0.6681 | 2.09 | 18000 | 1.5450 | 21.1981 | 18.6116 |
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+ | 0.6971 | 2.32 | 20000 | 1.5516 | 21.3101 | 18.892 |
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+ | 0.7283 | 2.55 | 22000 | 1.5405 | 20.902 | 18.6448 |
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+ | 0.7308 | 2.78 | 24000 | 1.5363 | 21.3017 | 18.2578 |
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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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