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gpt2
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README.md CHANGED
@@ -18,11 +18,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [riotu-lab/ArabianGPT-01B](https://huggingface.co/riotu-lab/ArabianGPT-01B) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.6229
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- - Bleu: 0.1607
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- - Rouge1: 0.4264
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- - Rouge2: 0.1631
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- - Rougel: 0.3675
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  ## Model description
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@@ -48,15 +48,30 @@ The following hyperparameters were used during training:
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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: 500
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- - num_epochs: 5.0
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Bleu | Rouge1 | Rouge2 | Rougel |
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- |:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:------:|
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- | 3.359 | 1.5674 | 500 | 3.1283 | 0.1142 | 0.3298 | 0.0843 | 0.2561 |
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- | 2.9208 | 3.1348 | 1000 | 2.7298 | 0.1491 | 0.4041 | 0.1430 | 0.3408 |
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- | 2.619 | 4.7022 | 1500 | 2.6229 | 0.1607 | 0.4264 | 0.1631 | 0.3675 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [riotu-lab/ArabianGPT-01B](https://huggingface.co/riotu-lab/ArabianGPT-01B) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.9086
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+ - Bleu: 0.3178
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+ - Rouge1: 0.5876
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+ - Rouge2: 0.3513
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+ - Rougel: 0.5510
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  ## Model description
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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: 500
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+ - num_epochs: 20.0
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  ### Training results
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+ | Training Loss | Epoch | Step | Bleu | Validation Loss | Rouge1 | Rouge2 | Rougel |
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+ |:-------------:|:-------:|:----:|:------:|:---------------:|:------:|:------:|:------:|
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+ | 3.359 | 1.5674 | 500 | 0.1142 | 3.1283 | 0.3298 | 0.0843 | 0.2561 |
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+ | 2.9208 | 3.1348 | 1000 | 0.1491 | 2.7298 | 0.4041 | 0.1430 | 0.3408 |
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+ | 2.619 | 4.7022 | 1500 | 0.1607 | 2.6229 | 0.4264 | 0.1631 | 0.3675 |
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+ | 2.4047 | 4.3384 | 2000 | 2.2002 | 0.2721 | 0.4976 | 0.2542 | 0.4506 |
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+ | 2.19 | 5.4230 | 2500 | 2.0992 | 0.2854 | 0.5205 | 0.2788 | 0.4773 |
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+ | 2.0473 | 6.5076 | 3000 | 2.0362 | 0.2929 | 0.5381 | 0.2965 | 0.4965 |
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+ | 1.9397 | 7.5922 | 3500 | 1.9933 | 0.2996 | 0.5494 | 0.3103 | 0.5102 |
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+ | 1.857 | 8.6768 | 4000 | 1.9647 | 0.3024 | 0.5598 | 0.3191 | 0.5203 |
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+ | 1.784 | 9.7614 | 4500 | 1.9443 | 0.3062 | 0.5675 | 0.3269 | 0.5279 |
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+ | 1.7239 | 10.8460 | 5000 | 1.9320 | 0.3099 | 0.5724 | 0.3339 | 0.5341 |
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+ | 1.6713 | 11.9306 | 5500 | 1.9206 | 0.3116 | 0.5765 | 0.3383 | 0.5387 |
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+ | 1.6263 | 13.0152 | 6000 | 1.9168 | 0.3127 | 0.5781 | 0.3416 | 0.5416 |
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+ | 1.5869 | 14.0998 | 6500 | 1.9148 | 0.3137 | 0.5829 | 0.3448 | 0.5451 |
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+ | 1.5544 | 15.1844 | 7000 | 1.9121 | 0.3158 | 0.5845 | 0.3476 | 0.5476 |
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+ | 1.5307 | 16.2690 | 7500 | 1.9106 | 0.3165 | 0.5853 | 0.3488 | 0.5486 |
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+ | 1.5087 | 17.3536 | 8000 | 1.9093 | 0.3169 | 0.5861 | 0.3504 | 0.5500 |
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+ | 1.4937 | 18.4382 | 8500 | 1.9084 | 0.3172 | 0.5869 | 0.3505 | 0.5504 |
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+ | 1.4824 | 19.5228 | 9000 | 1.9086 | 0.3178 | 0.5876 | 0.3513 | 0.5510 |
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  ### Framework versions
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