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--- |
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language: |
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- ko |
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- ja |
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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: tst-translation-output |
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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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# tst-translation-output |
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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: 0.8968 |
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- Bleu: 9.457 |
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- Gen Len: 17.4895 |
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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: 2 |
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- eval_batch_size: 2 |
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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: 4 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 8 |
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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: 1500 |
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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Bleu | Gen Len | Validation Loss | |
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|:-------------:|:-----:|:-----:|:-------:|:-------:|:---------------:| |
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| 1.1751 | 0.47 | 3000 | 7.6766 | 17.4644 | 1.1289 | |
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| 1.0268 | 0.93 | 6000 | 9.2277 | 17.7668 | 0.9895 | |
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| 0.8075 | 1.4 | 9000 | 9.1197 | 17.6811 | 0.9457 | |
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| 0.8082 | 1.87 | 12000 | 8.4837 | 17.4826 | 0.9053 | |
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| 0.5841 | 2.33 | 15000 | 9.8887 | 17.5166 | 0.9303 | |
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| 0.6142 | 2.8 | 18000 | 9.547 | 17.426 | 0.9142 | |
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| 0.4119 | 3.26 | 21000 | 9.5055 | 17.3378 | 0.9879 | |
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| 0.2837 | 7.46 | 24000 | 11.0549 | 17.2982 | 1.0063 | |
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| 0.1792 | 8.4 | 27000 | 8.9031 | 17.2801 | 1.0856 | |
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| 0.1204 | 9.33 | 30000 | 1.1643 | 11.3498 | 17.2986 | |
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| 0.0826 | 10.26 | 33000 | 1.2319 | 10.796 | 17.3627 | |
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| 0.0617 | 11.19 | 36000 | 1.2785 | 10.6211 | 17.3748 | |
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| 0.0523 | 12.13 | 39000 | 1.3217 | 9.8848 | 17.3358 | |
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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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