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language: |
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- en |
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- ko |
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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: mbartLarge_mid_en-ko1 |
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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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# mbartLarge_mid_en-ko1 |
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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: 1.4106 |
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- Bleu: 13.2758 |
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- Gen Len: 16.235 |
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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 |
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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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| 1.5855 | 1.12 | 1500 | 1.5215 | 11.5186 | 16.204 | |
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| 1.4287 | 2.24 | 3000 | 1.4549 | 12.2855 | 16.1497 | |
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| 1.2937 | 3.37 | 4500 | 1.4250 | 12.6484 | 16.2152 | |
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| 1.2444 | 4.49 | 6000 | 1.4165 | 13.0063 | 16.0749 | |
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| 1.1335 | 5.61 | 7500 | 1.4106 | 13.2758 | 16.235 | |
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| 1.0508 | 6.73 | 9000 | 1.4243 | 13.0601 | 15.86 | |
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| 0.9462 | 7.86 | 10500 | 1.4497 | 13.0828 | 16.0475 | |
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| 0.8464 | 8.98 | 12000 | 1.4692 | 13.5878 | 15.9308 | |
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| 0.6995 | 10.1 | 13500 | 1.5572 | 13.1085 | 15.9906 | |
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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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