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--- |
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tags: |
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- generated_from_trainer |
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base_model: jq/nllb-1.3B-many-to-many-step-2k |
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datasets: |
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- generator |
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model-index: |
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- name: nllb-1.3B-many-to-many-pronouncorrection-charaug |
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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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# nllb-1.3B-many-to-many-pronouncorrection-charaug |
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This model is a fine-tuned version of [jq/nllb-1.3B-many-to-many-step-2k](https://huggingface.co/jq/nllb-1.3B-many-to-many-step-2k) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2075 |
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- Bleu Ach Eng: 28.371 |
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- Bleu Lgg Eng: 30.45 |
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- Bleu Lug Eng: 41.978 |
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- Bleu Nyn Eng: 32.296 |
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- Bleu Teo Eng: 30.422 |
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- Bleu Eng Ach: 20.972 |
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- Bleu Eng Lgg: 22.362 |
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- Bleu Eng Lug: 30.359 |
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- Bleu Eng Nyn: 15.305 |
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- Bleu Eng Teo: 21.391 |
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- Bleu Mean: 27.391 |
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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: 0.0003 |
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- train_batch_size: 25 |
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- eval_batch_size: 25 |
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- seed: 42 |
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- gradient_accumulation_steps: 120 |
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- total_train_batch_size: 3000 |
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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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- training_steps: 1500 |
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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 Ach Eng | Bleu Lgg Eng | Bleu Lug Eng | Bleu Nyn Eng | Bleu Teo Eng | Bleu Eng Ach | Bleu Eng Lgg | Bleu Eng Lug | Bleu Eng Nyn | Bleu Eng Teo | Bleu Mean | |
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|:-------------:|:------:|:----:|:---------------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------------:|:------------:|:---------:| |
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| No log | 0.0667 | 100 | 1.1541 | 29.033 | 31.47 | 41.596 | 34.169 | 32.442 | 19.677 | 19.657 | 27.889 | 14.554 | 19.143 | 26.963 | |
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| No log | 1.0301 | 200 | 1.1570 | 27.473 | 31.853 | 41.934 | 32.575 | 31.606 | 20.25 | 20.634 | 28.592 | 13.672 | 19.997 | 26.859 | |
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| No log | 1.0968 | 300 | 1.1288 | 29.086 | 33.257 | 43.387 | 33.678 | 33.579 | 20.377 | 20.91 | 28.906 | 14.992 | 21.013 | 27.919 | |
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| No log | 2.0603 | 400 | 1.1620 | 28.122 | 31.46 | 42.491 | 33.304 | 32.331 | 20.282 | 21.604 | 29.577 | 14.961 | 20.94 | 27.507 | |
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| 0.7273 | 3.0237 | 500 | 1.1661 | 28.311 | 32.122 | 42.825 | 32.333 | 32.415 | 19.799 | 22.287 | 29.558 | 15.708 | 21.948 | 27.731 | |
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| 0.7273 | 3.0904 | 600 | 1.1652 | 28.593 | 30.62 | 41.964 | 33.383 | 32.08 | 21.142 | 21.8 | 30.215 | 14.717 | 21.744 | 27.626 | |
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| 0.7273 | 4.0538 | 700 | 1.2075 | 28.371 | 30.45 | 41.978 | 32.296 | 30.422 | 20.972 | 22.362 | 30.359 | 15.305 | 21.391 | 27.391 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.2.0 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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