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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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<!-- 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_exp10p |
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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: 1.1283 |
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- Bleu: 28.8237 |
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- Gen Len: 18.5382 |
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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_with_restarts |
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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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| 1.4782 | 0.31 | 2000 | 1.4360 | 21.538 | 18.6032 | |
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| 1.3618 | 0.62 | 4000 | 1.3226 | 23.8354 | 18.5594 | |
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| 1.2983 | 0.93 | 6000 | 1.2637 | 25.0795 | 18.7894 | |
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| 1.2065 | 1.24 | 8000 | 1.2371 | 25.7409 | 18.5615 | |
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| 1.1926 | 1.55 | 10000 | 1.2116 | 26.0527 | 18.4019 | |
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| 1.1734 | 1.86 | 12000 | 1.1907 | 26.9802 | 18.6141 | |
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| 1.0677 | 2.17 | 14000 | 1.1802 | 27.1925 | 18.4547 | |
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| 1.0773 | 2.48 | 16000 | 1.1655 | 27.5641 | 18.6726 | |
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| 1.0688 | 2.78 | 18000 | 1.1521 | 27.6261 | 18.6127 | |
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| 0.9542 | 3.09 | 20000 | 1.1709 | 27.16 | 18.3782 | |
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| 0.9531 | 3.4 | 22000 | 1.1435 | 28.0684 | 18.436 | |
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| 0.9756 | 3.71 | 24000 | 1.1565 | 27.6025 | 18.7284 | |
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| 0.9964 | 4.02 | 26000 | 1.2285 | 25.6999 | 18.3255 | |
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| 0.9721 | 4.33 | 28000 | 1.1881 | 27.3499 | 18.5409 | |
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| 0.9237 | 4.64 | 30000 | 1.1497 | 28.2692 | 18.6614 | |
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| 0.9041 | 4.95 | 32000 | 1.1283 | 28.8215 | 18.5493 | |
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| 0.6842 | 5.26 | 34000 | 1.1741 | 28.6873 | 18.515 | |
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| 0.7101 | 5.57 | 36000 | 1.1876 | 28.0778 | 18.3422 | |
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| 0.7697 | 5.88 | 38000 | 1.1898 | 27.6338 | 18.6766 | |
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| 0.6028 | 6.19 | 40000 | 1.2393 | 28.0713 | 18.5903 | |
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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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