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yesj1234
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ko-en_mbartLarge_exp20p_batch64_linear

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 +74 -0
  3. added_tokens.json +59 -0
  4. all_results.json +22 -0
  5. checkpoint-8000/added_tokens.json +59 -0
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.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_exp20p_batch64_linear
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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_exp20p_batch64_linear
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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: 1.2042
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+ - Bleu: 27.8215
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+ - Gen Len: 18.6731
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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: 2
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+ - eval_batch_size: 2
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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: 8
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+ - total_train_batch_size: 64
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+ - total_eval_batch_size: 8
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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: 2000
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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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+ | 1.0585 | 1.86 | 4000 | 1.1435 | 27.494 | 18.9136 |
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+ | 0.6719 | 3.71 | 8000 | 1.2042 | 27.8203 | 18.6815 |
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+ | 0.3964 | 5.57 | 12000 | 1.4261 | 27.1711 | 18.5184 |
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+ | 0.2282 | 7.43 | 16000 | 1.7275 | 26.1891 | 18.5479 |
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+ | 0.1338 | 9.28 | 20000 | 1.9251 | 26.1533 | 18.505 |
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+ | 0.1033 | 11.14 | 24000 | 2.0758 | 26.0643 | 18.4275 |
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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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