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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: 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: 1.4429 |
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- Bleu: 21.4825 |
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- Gen Len: 18.792 |
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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: 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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| 1.3784 | 0.23 | 2000 | 1.5514 | 18.2602 | 19.2938 | |
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| 1.2953 | 0.46 | 4000 | 1.5006 | 19.6277 | 18.7905 | |
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| 1.2446 | 0.7 | 6000 | 1.4664 | 20.2667 | 19.2503 | |
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| 1.2095 | 0.93 | 8000 | 1.4482 | 20.8962 | 18.9352 | |
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| 0.9279 | 1.16 | 10000 | 1.4799 | 20.9876 | 19.093 | |
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| 0.9604 | 1.39 | 12000 | 1.4672 | 21.261 | 18.8735 | |
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| 0.9543 | 1.62 | 14000 | 1.4611 | 21.1987 | 18.8396 | |
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| 0.9532 | 1.86 | 16000 | 1.4429 | 21.4802 | 18.8239 | |
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| 0.6681 | 2.09 | 18000 | 1.5450 | 21.1981 | 18.6116 | |
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| 0.6971 | 2.32 | 20000 | 1.5516 | 21.3101 | 18.892 | |
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| 0.7283 | 2.55 | 22000 | 1.5405 | 20.902 | 18.6448 | |
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| 0.7308 | 2.78 | 24000 | 1.5363 | 21.3017 | 18.2578 | |
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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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