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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_exp5p_linear |
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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_exp5p_linear |
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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: 1.2308 |
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- Bleu: 26.2764 |
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- Gen Len: 18.3888 |
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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: linear |
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- lr_scheduler_warmup_steps: 500 |
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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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| 1.7665 | 0.46 | 1000 | 1.6564 | 17.6773 | 18.7196 | |
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| 1.5688 | 0.93 | 2000 | 1.4939 | 20.8837 | 18.3983 | |
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| 1.457 | 1.39 | 3000 | 1.4350 | 21.9168 | 18.458 | |
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| 1.4107 | 1.86 | 4000 | 1.3752 | 22.8881 | 18.4826 | |
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| 1.3039 | 2.32 | 5000 | 1.3327 | 23.8115 | 18.4348 | |
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| 1.282 | 2.78 | 6000 | 1.3079 | 24.235 | 18.3561 | |
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| 1.2133 | 3.25 | 7000 | 1.2820 | 24.8877 | 18.5204 | |
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| 1.1787 | 3.71 | 8000 | 1.2580 | 25.2719 | 18.415 | |
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| 1.1154 | 4.18 | 9000 | 1.2543 | 25.5507 | 18.3528 | |
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| 1.0956 | 4.64 | 10000 | 1.2415 | 25.7284 | 18.5348 | |
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| 1.023 | 5.1 | 11000 | 1.2410 | 25.7912 | 18.3347 | |
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| 0.95 | 5.57 | 12000 | 1.2327 | 25.9921 | 18.2593 | |
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| 0.9476 | 6.03 | 13000 | 1.2631 | 25.829 | 18.3686 | |
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| 0.9061 | 6.5 | 14000 | 1.2548 | 25.8316 | 18.7481 | |
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| 0.9037 | 6.96 | 15000 | 1.2308 | 26.2764 | 18.3888 | |
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| 0.7431 | 7.42 | 16000 | 1.2716 | 25.9268 | 18.256 | |
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| 0.7526 | 7.89 | 17000 | 1.2655 | 25.9883 | 18.2052 | |
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| 0.6654 | 8.35 | 18000 | 1.3118 | 25.6866 | 18.2217 | |
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| 0.6953 | 8.82 | 19000 | 1.3050 | 25.8958 | 18.3387 | |
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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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