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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-output2 |
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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-output2 |
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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: 0.9049 |
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- Bleu: 10.3643 |
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- Gen Len: 17.4046 |
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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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- total_train_batch_size: 16 |
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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: 35 |
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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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| 1.2499 | 0.23 | 1500 | 1.1806 | 6.1112 | 18.0495 | |
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| 1.1007 | 0.46 | 3000 | 1.0686 | 7.4845 | 17.6068 | |
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| 1.0334 | 0.68 | 4500 | 1.0013 | 9.0076 | 17.6214 | |
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| 0.992 | 0.91 | 6000 | 0.9599 | 8.6786 | 17.868 | |
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| 0.7881 | 1.14 | 7500 | 0.9644 | 9.2343 | 17.2061 | |
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| 0.7675 | 1.37 | 9000 | 0.9427 | 10.0578 | 17.6006 | |
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| 0.7665 | 1.59 | 10500 | 0.9238 | 10.436 | 17.2095 | |
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| 0.7707 | 1.82 | 12000 | 0.9049 | 10.5971 | 17.2971 | |
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| 0.6119 | 2.05 | 13500 | 0.9392 | 10.8369 | 17.3201 | |
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| 0.5579 | 2.28 | 15000 | 0.9429 | 10.3486 | 17.3221 | |
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| 0.5633 | 2.5 | 16500 | 0.9310 | 10.6114 | 17.3679 | |
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| 0.5764 | 2.73 | 18000 | 0.9265 | 9.9612 | 17.1339 | |
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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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