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--- |
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language: |
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- ja |
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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: jako_mbartLarge_6p_run1 |
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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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# jako_mbartLarge_6p_run1 |
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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: 1.1539 |
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- Bleu: 26.2658 |
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- Gen Len: 19.3961 |
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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: linear |
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- lr_scheduler_warmup_steps: 300 |
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- num_epochs: 10 |
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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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| 1.4641 | 0.48 | 1000 | 1.3276 | 21.6162 | 19.4434 | |
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| 1.2615 | 0.96 | 2000 | 1.1866 | 24.346 | 19.4734 | |
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| 0.9103 | 1.44 | 3000 | 1.1638 | 25.4249 | 19.0086 | |
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| 0.8285 | 1.92 | 4000 | 1.1539 | 26.2658 | 19.3961 | |
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| 0.5977 | 2.4 | 5000 | 1.1978 | 25.5651 | 19.6248 | |
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| 0.5423 | 2.88 | 6000 | 1.1830 | 26.8441 | 19.1349 | |
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| 0.3816 | 3.36 | 7000 | 1.2670 | 26.1301 | 19.1207 | |
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| 0.3412 | 3.84 | 8000 | 1.2870 | 26.7783 | 19.2417 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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