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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_linear_alpha |
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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_exp20p_linear_alpha |
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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: 1.1682 |
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- Bleu: 29.1144 |
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- Gen Len: 18.5459 |
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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: 5.5e-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: linear |
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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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| 1.404 | 0.46 | 4000 | 1.3738 | 22.5375 | 18.6852 | |
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| 1.2629 | 0.93 | 8000 | 1.2458 | 25.3741 | 18.7797 | |
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| 1.1951 | 1.39 | 12000 | 1.2067 | 26.1281 | 18.6597 | |
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| 1.1317 | 1.86 | 16000 | 1.1768 | 26.5384 | 19.2055 | |
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| 0.9906 | 2.32 | 20000 | 1.1363 | 28.2459 | 18.7269 | |
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| 0.9894 | 2.78 | 24000 | 1.1239 | 28.5124 | 18.6882 | |
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| 0.8965 | 3.25 | 28000 | 1.1278 | 28.5335 | 18.4917 | |
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| 0.9138 | 3.71 | 32000 | 1.1216 | 28.8189 | 18.7873 | |
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| 0.8272 | 4.18 | 36000 | 1.1468 | 28.332 | 18.6516 | |
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| 0.8753 | 4.64 | 40000 | 1.1345 | 28.2695 | 18.4919 | |
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| 0.6855 | 5.11 | 44000 | 1.1542 | 28.7913 | 18.7596 | |
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| 0.7088 | 5.57 | 48000 | 1.1531 | 29.0865 | 18.6626 | |
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| 0.6738 | 6.03 | 52000 | 1.1906 | 28.0235 | 18.4243 | |
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| 0.6763 | 6.5 | 56000 | 1.1941 | 28.1501 | 18.6932 | |
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| 0.6594 | 6.96 | 60000 | 1.1682 | 29.1144 | 18.5459 | |
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| 0.5971 | 7.43 | 64000 | 1.2449 | 27.9464 | 18.4482 | |
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| 0.5935 | 7.89 | 68000 | 1.2156 | 28.6034 | 18.5967 | |
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| 0.5383 | 8.35 | 72000 | 1.2927 | 27.891 | 18.6539 | |
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| 0.6022 | 8.82 | 76000 | 1.2831 | 27.7624 | 18.5558 | |
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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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