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--- |
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language: |
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- tok |
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- en |
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- multilingual |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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- translation |
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metrics: |
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- bleu |
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widget: |
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- text: toki! mi jan Ton. mi lon ma Tawan. |
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- text: soweli li toki ala toki e toki Inli? |
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model-index: |
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- name: toki-en-mt |
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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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# toki-en-mt |
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ROMANCE-en](https://huggingface.co/Helsinki-NLP/opus-mt-ROMANCE-en) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2840 |
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- Bleu: 26.7612 |
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- Gen Len: 9.0631 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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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: 10 |
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- mixed_precision_training: Native AMP |
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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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| 1.7228 | 1.0 | 1260 | 1.4572 | 19.9464 | 9.2177 | |
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| 1.3182 | 2.0 | 2520 | 1.3356 | 22.4628 | 9.1263 | |
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| 1.1241 | 3.0 | 3780 | 1.3028 | 23.5152 | 9.0462 | |
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| 0.9995 | 4.0 | 5040 | 1.2784 | 23.9526 | 9.1697 | |
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| 0.8945 | 5.0 | 6300 | 1.2739 | 24.7707 | 9.0914 | |
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| 0.8331 | 6.0 | 7560 | 1.2725 | 25.3477 | 9.0518 | |
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| 0.7641 | 7.0 | 8820 | 1.2770 | 26.165 | 9.0245 | |
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| 0.7163 | 8.0 | 10080 | 1.2809 | 25.8053 | 9.0933 | |
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| 0.6886 | 9.0 | 11340 | 1.2799 | 26.5752 | 9.0669 | |
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| 0.6627 | 10.0 | 12600 | 1.2840 | 26.7612 | 9.0631 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.11.0 |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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