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Kumshe
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t5-small-finetuned-english-to-hausa

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  1. README.md +38 -11
  2. runs/Aug30_02-56-01_30190107fae3/events.out.tfevents.1724986564.30190107fae3.3467.0 +2 -2
README.md CHANGED
@@ -19,9 +19,9 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.6792
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- - Bleu: 64.4045
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- - Gen Len: 14.4721
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  ## Model description
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@@ -45,18 +45,45 @@ The following hyperparameters were used during training:
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  - eval_batch_size: 32
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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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- - lr_scheduler_warmup_steps: 1000
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- - num_epochs: 3
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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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- | 2.5691 | 1.0 | 749 | 1.2064 | 49.1383 | 15.0242 |
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- | 1.0998 | 2.0 | 1498 | 0.7609 | 61.7452 | 14.4781 |
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- | 0.7625 | 3.0 | 2247 | 0.6792 | 64.4045 | 14.4721 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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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: 0.7088
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+ - Bleu: 71.7187
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+ - Gen Len: 14.3652
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  ## Model description
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  - eval_batch_size: 32
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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: 3000
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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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+ | 3.1612 | 1.0 | 749 | 1.7523 | 32.7424 | 15.2302 |
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+ | 1.5573 | 2.0 | 1498 | 1.0553 | 53.4401 | 14.5568 |
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+ | 1.0462 | 3.0 | 2247 | 0.7899 | 60.8893 | 14.71 |
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+ | 0.8071 | 4.0 | 2996 | 0.6780 | 64.3438 | 14.4066 |
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+ | 0.6602 | 5.0 | 3745 | 0.6089 | 66.0887 | 14.127 |
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+ | 0.5562 | 6.0 | 4494 | 0.5741 | 66.8902 | 14.1295 |
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+ | 0.4872 | 7.0 | 5243 | 0.5497 | 68.4261 | 14.3395 |
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+ | 0.4299 | 8.0 | 5992 | 0.5412 | 68.9385 | 14.3446 |
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+ | 0.3872 | 9.0 | 6741 | 0.5377 | 69.5675 | 14.2603 |
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+ | 0.3478 | 10.0 | 7490 | 0.5356 | 70.0045 | 14.3615 |
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+ | 0.3147 | 11.0 | 8239 | 0.5312 | 70.1895 | 14.4524 |
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+ | 0.2848 | 12.0 | 8988 | 0.5484 | 70.8151 | 14.366 |
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+ | 0.2584 | 13.0 | 9737 | 0.5523 | 70.6127 | 14.2939 |
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+ | 0.2342 | 14.0 | 10486 | 0.5642 | 70.7368 | 14.3301 |
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+ | 0.2122 | 15.0 | 11235 | 0.5775 | 70.9399 | 14.3635 |
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+ | 0.1928 | 16.0 | 11984 | 0.5935 | 71.2577 | 14.352 |
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+ | 0.1757 | 17.0 | 12733 | 0.5964 | 71.2056 | 14.3929 |
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+ | 0.1608 | 18.0 | 13482 | 0.6085 | 71.0265 | 14.3877 |
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+ | 0.1475 | 19.0 | 14231 | 0.6219 | 71.5491 | 14.3812 |
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+ | 0.1352 | 20.0 | 14980 | 0.6285 | 71.5971 | 14.3675 |
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+ | 0.1237 | 21.0 | 15729 | 0.6468 | 71.4863 | 14.3782 |
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+ | 0.1142 | 22.0 | 16478 | 0.6652 | 71.5849 | 14.3734 |
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+ | 0.1082 | 23.0 | 17227 | 0.6733 | 71.6037 | 14.3298 |
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+ | 0.0998 | 24.0 | 17976 | 0.6852 | 71.6926 | 14.4066 |
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+ | 0.0962 | 25.0 | 18725 | 0.6899 | 71.7003 | 14.358 |
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+ | 0.0915 | 26.0 | 19474 | 0.6994 | 71.6191 | 14.3702 |
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+ | 0.0882 | 27.0 | 20223 | 0.7033 | 71.5731 | 14.3537 |
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+ | 0.0857 | 28.0 | 20972 | 0.7084 | 71.6407 | 14.3618 |
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+ | 0.0853 | 29.0 | 21721 | 0.7086 | 71.7115 | 14.3635 |
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+ | 0.0847 | 30.0 | 22470 | 0.7088 | 71.7187 | 14.3652 |
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  ### Framework versions
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