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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_mid2 |
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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_mid2 |
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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: 1.3246 |
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- Bleu: 22.9623 |
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- Gen Len: 18.7197 |
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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: 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: 1000 |
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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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| 1.5377 | 0.23 | 2000 | 1.6122 | 17.2009 | 18.7106 | |
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| 1.3891 | 0.46 | 4000 | 1.5059 | 19.3345 | 18.7688 | |
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| 1.2812 | 0.7 | 6000 | 1.4348 | 20.6032 | 18.9022 | |
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| 1.2374 | 0.93 | 8000 | 1.4035 | 21.2391 | 18.8434 | |
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| 1.1734 | 1.16 | 10000 | 1.4039 | 21.304 | 18.9964 | |
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| 1.1531 | 1.39 | 12000 | 1.3694 | 21.9087 | 18.8573 | |
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| 1.1158 | 1.62 | 14000 | 1.3574 | 22.004 | 18.5485 | |
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| 1.0941 | 1.86 | 16000 | 1.3457 | 21.9785 | 18.7119 | |
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| 0.9809 | 2.09 | 18000 | 1.3495 | 22.7983 | 18.8011 | |
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| 0.9834 | 2.32 | 20000 | 1.3429 | 22.5654 | 18.9416 | |
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| 0.9981 | 2.55 | 22000 | 1.3246 | 22.9493 | 18.7364 | |
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| 1.0074 | 2.78 | 24000 | 1.3539 | 22.3874 | 18.4428 | |
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| 0.9752 | 3.02 | 26000 | 1.3587 | 22.1907 | 18.8139 | |
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| 0.8858 | 3.25 | 28000 | 1.3457 | 22.82 | 18.8021 | |
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| 0.8895 | 3.48 | 30000 | 1.3603 | 22.1575 | 18.5638 | |
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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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