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--- |
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license: mit |
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base_model: MT-Informal-Languages/Helsinki-NLP-opus-mt-ug |
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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: Helsinki_lg_inf_en |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/asr-africa-research-team/huggingface/runs/0gisv7pm) |
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# Helsinki_lg_inf_en |
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This model is a fine-tuned version of [MT-Informal-Languages/Helsinki-NLP-opus-mt-ug](https://huggingface.co/MT-Informal-Languages/Helsinki-NLP-opus-mt-ug) on the Luganda Formal Data dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0505 |
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- Bleu: 57.3885 |
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- Gen Len: 17.3595 |
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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: 30 |
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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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| No log | 1.0 | 153 | 0.4708 | 0.9369 | 19.2244 | |
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| No log | 2.0 | 306 | 0.4227 | 1.1005 | 20.8706 | |
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| No log | 3.0 | 459 | 0.3854 | 1.4207 | 19.8702 | |
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| 1.1563 | 4.0 | 612 | 0.3519 | 1.7877 | 19.5442 | |
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| 1.1563 | 5.0 | 765 | 0.3216 | 2.4366 | 18.7977 | |
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| 1.1563 | 6.0 | 918 | 0.2929 | 3.0827 | 18.6413 | |
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| 0.375 | 7.0 | 1071 | 0.2677 | 3.9367 | 19.2035 | |
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| 0.375 | 8.0 | 1224 | 0.2427 | 5.605 | 18.5111 | |
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| 0.375 | 9.0 | 1377 | 0.2192 | 7.0359 | 18.6204 | |
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| 0.2959 | 10.0 | 1530 | 0.1980 | 9.5819 | 17.8284 | |
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| 0.2959 | 11.0 | 1683 | 0.1794 | 11.9364 | 17.7428 | |
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| 0.2959 | 12.0 | 1836 | 0.1621 | 13.9353 | 18.0643 | |
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| 0.2959 | 13.0 | 1989 | 0.1464 | 16.9189 | 17.8714 | |
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| 0.2334 | 14.0 | 2142 | 0.1315 | 19.2848 | 18.0201 | |
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| 0.2334 | 15.0 | 2295 | 0.1189 | 22.6041 | 17.973 | |
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| 0.2334 | 16.0 | 2448 | 0.1085 | 25.554 | 18.0324 | |
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| 0.1848 | 17.0 | 2601 | 0.0992 | 28.6049 | 17.4644 | |
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| 0.1848 | 18.0 | 2754 | 0.0905 | 31.9759 | 17.8104 | |
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| 0.1848 | 19.0 | 2907 | 0.0828 | 35.5846 | 17.8108 | |
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| 0.1507 | 20.0 | 3060 | 0.0764 | 39.748 | 17.656 | |
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| 0.1507 | 21.0 | 3213 | 0.0712 | 42.3511 | 17.5602 | |
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| 0.1507 | 22.0 | 3366 | 0.0665 | 45.7843 | 17.5238 | |
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| 0.1285 | 23.0 | 3519 | 0.0628 | 48.4047 | 17.5233 | |
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| 0.1285 | 24.0 | 3672 | 0.0592 | 50.5559 | 17.3403 | |
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| 0.1285 | 25.0 | 3825 | 0.0564 | 52.0378 | 17.4443 | |
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| 0.1285 | 26.0 | 3978 | 0.0545 | 54.0726 | 17.579 | |
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| 0.1132 | 27.0 | 4131 | 0.0526 | 55.201 | 17.4017 | |
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| 0.1132 | 28.0 | 4284 | 0.0515 | 56.6048 | 17.4447 | |
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| 0.1132 | 29.0 | 4437 | 0.0508 | 57.2182 | 17.448 | |
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| 0.1047 | 30.0 | 4590 | 0.0505 | 57.3885 | 17.3595 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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