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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: ./reduced_model |
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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 [mbart-large-cc25](https://huggingface.co/facebook/mbart-large-cc25) on an custom dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.7663 |
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- Bleu: 19.3382 |
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- Gen Len: 17.8929 |
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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: 16 |
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- total_train_batch_size: 128 |
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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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- 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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| 2.6161 | 11.09 | 2000 | 3.1762 | 13.5109 | 19.1966 | |
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| 2.6161 | 13.86 | 2500 | 3.0375 | 16.2868 | 18.7985 | |
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| 1.4467 | 16.62 | 3000 | 3.1328 | 17.6991 | 18.1949 | |
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| 1.4467 | 19.39 | 3500 | 3.2690 | 17.9052 | 18.3117 | |
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| 0.6809 | 22.15 | 4000 | 3.3850 | 18.4075 | 18.2149 | |
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| 0.6809 | 24.91 | 4500 | 3.4465 | 19.0339 | 18.009 | |
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| 0.3422 | 27.68 | 5000 | 3.5680 | 18.7281 | 17.5902 | |
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| 0.3422 | 30.44 | 5500 | 3.6350 | 19.1534 | 18.2177 | |
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| 0.1941 | 33.2 | 6000 | 3.7153 | 19.2575 | 17.8784 | |
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| 0.1941 | 35.97 | 6500 | 3.7382 | 19.2475 | 17.9831 | |
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| 0.1271 | 38.73 | 7000 | 3.7573 | 19.3045 | 17.9889 | |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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