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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google-t5/t5-small |
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tags: |
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- translation |
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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: t5-small-finetuned-hausa-to-chinese |
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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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# t5-small-finetuned-hausa-to-chinese |
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This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3817 |
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- Bleu: 30.2633 |
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- Gen Len: 3.5559 |
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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: 0.0008 |
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- train_batch_size: 32 |
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- eval_batch_size: 64 |
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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: cosine |
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- lr_scheduler_warmup_steps: 4000 |
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- num_epochs: 20 |
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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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| 0.6981 | 1.0 | 846 | 0.2900 | 14.2476 | 3.4917 | |
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| 0.3149 | 2.0 | 1692 | 0.2639 | 18.6104 | 3.4725 | |
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| 0.2782 | 3.0 | 2538 | 0.2467 | 9.1092 | 3.2542 | |
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| 0.2622 | 4.0 | 3384 | 0.2481 | 24.1345 | 3.4047 | |
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| 0.2428 | 5.0 | 4230 | 0.2529 | 16.9217 | 3.3965 | |
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| 0.2271 | 6.0 | 5076 | 0.2491 | 27.8491 | 3.5349 | |
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| 0.2047 | 7.0 | 5922 | 0.2507 | 16.6565 | 3.339 | |
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| 0.1902 | 8.0 | 6768 | 0.2506 | 25.6462 | 3.5667 | |
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| 0.1739 | 9.0 | 7614 | 0.2610 | 27.1673 | 3.5916 | |
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| 0.1587 | 10.0 | 8460 | 0.2438 | 29.306 | 3.5839 | |
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| 0.1425 | 11.0 | 9306 | 0.2660 | 29.08 | 3.6478 | |
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| 0.1251 | 12.0 | 10152 | 0.2721 | 29.9148 | 3.4994 | |
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| 0.1105 | 13.0 | 10998 | 0.2929 | 28.1895 | 3.5526 | |
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| 0.0956 | 14.0 | 11844 | 0.3010 | 30.552 | 3.5717 | |
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| 0.083 | 15.0 | 12690 | 0.3307 | 27.9728 | 3.5303 | |
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| 0.0724 | 16.0 | 13536 | 0.3404 | 27.1874 | 3.5146 | |
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| 0.0652 | 17.0 | 14382 | 0.3592 | 29.9567 | 3.5529 | |
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| 0.0568 | 18.0 | 15228 | 0.3774 | 30.5145 | 3.5668 | |
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| 0.0549 | 19.0 | 16074 | 0.3795 | 30.6604 | 3.5637 | |
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| 0.0526 | 20.0 | 16920 | 0.3817 | 30.2633 | 3.5559 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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