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oddadmix/bi-msa-egyptian-translator-masrawy

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README.md CHANGED
@@ -14,7 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [UBC-NLP/AraT5v2-base-1024](https://huggingface.co/UBC-NLP/AraT5v2-base-1024) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.5331
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  ## Model description
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@@ -41,7 +41,7 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 64
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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: 5
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  ### Training results
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@@ -86,6 +86,29 @@ The following hyperparameters were used during training:
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  | 1.9764 | 4.72 | 18500 | 1.5331 |
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  | 1.9808 | 4.85 | 19000 | 1.5334 |
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  | 1.9739 | 4.98 | 19500 | 1.5331 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [UBC-NLP/AraT5v2-base-1024](https://huggingface.co/UBC-NLP/AraT5v2-base-1024) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.4636
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  ## Model description
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  - total_train_batch_size: 64
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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: 8
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  ### Training results
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  | 1.9764 | 4.72 | 18500 | 1.5331 |
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  | 1.9808 | 4.85 | 19000 | 1.5334 |
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  | 1.9739 | 4.98 | 19500 | 1.5331 |
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+ | 1.9662 | 5.1 | 20000 | 1.5374 |
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+ | 1.9696 | 5.23 | 20500 | 1.5322 |
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+ | 1.9535 | 5.36 | 21000 | 1.5301 |
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+ | 1.9555 | 5.49 | 21500 | 1.5271 |
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+ | 1.9459 | 5.61 | 22000 | 1.5255 |
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+ | 1.9548 | 5.74 | 22500 | 1.5205 |
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+ | 1.9538 | 5.87 | 23000 | 1.5171 |
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+ | 1.9409 | 6.0 | 23500 | 1.5158 |
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+ | 1.918 | 6.12 | 24000 | 1.5129 |
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+ | 1.9415 | 6.25 | 24500 | 1.5102 |
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+ | 1.9168 | 6.38 | 25000 | 1.5097 |
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+ | 1.9131 | 6.51 | 25500 | 1.5093 |
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+ | 1.9205 | 6.63 | 26000 | 1.5068 |
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+ | 1.913 | 6.76 | 26500 | 1.5058 |
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+ | 1.9098 | 6.89 | 27000 | 1.4675 |
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+ | 1.9093 | 7.02 | 27500 | 1.4663 |
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+ | 1.9044 | 7.14 | 28000 | 1.4656 |
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+ | 1.9047 | 7.27 | 28500 | 1.4650 |
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+ | 1.9103 | 7.4 | 29000 | 1.4641 |
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+ | 1.9002 | 7.53 | 29500 | 1.4637 |
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+ | 1.8961 | 7.66 | 30000 | 1.4641 |
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+ | 1.895 | 7.78 | 30500 | 1.4638 |
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+ | 1.9073 | 7.91 | 31000 | 1.4636 |
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  ### Framework versions
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