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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 |
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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 |
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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: 1.1451 |
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- Bleu: 28.9507 |
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- Gen Len: 18.6702 |
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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: 2000 |
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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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| 1.4008 | 0.46 | 4000 | 1.3739 | 22.7174 | 18.7094 | |
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| 1.2847 | 0.93 | 8000 | 1.2652 | 24.8557 | 18.7254 | |
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| 1.2009 | 1.39 | 12000 | 1.2082 | 26.2074 | 18.7513 | |
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| 1.1686 | 1.86 | 16000 | 1.1841 | 26.304 | 19.161 | |
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| 1.0205 | 2.32 | 20000 | 1.1441 | 27.8937 | 18.6638 | |
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| 1.0217 | 2.78 | 24000 | 1.1301 | 28.4149 | 18.6666 | |
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| 0.8876 | 3.25 | 28000 | 1.1270 | 28.5803 | 18.6229 | |
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| 0.9024 | 3.71 | 32000 | 1.1181 | 28.852 | 18.7813 | |
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| 0.7927 | 4.18 | 36000 | 1.1393 | 28.3975 | 18.4863 | |
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| 0.8174 | 4.64 | 40000 | 1.1249 | 28.6313 | 18.3916 | |
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| 0.7434 | 5.11 | 44000 | 1.1696 | 28.2898 | 18.7739 | |
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| 0.7416 | 5.57 | 48000 | 1.1451 | 28.9507 | 18.6744 | |
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| 0.689 | 6.03 | 52000 | 1.1759 | 28.3532 | 18.4481 | |
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| 0.7238 | 6.5 | 56000 | 1.1825 | 28.3827 | 18.7038 | |
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| 0.7238 | 6.96 | 60000 | 1.1676 | 28.8248 | 18.5073 | |
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| 0.657 | 7.43 | 64000 | 1.2514 | 27.4378 | 18.4196 | |
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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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