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res_nw_dj

Safetensors
gpt2
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  2. model.safetensors +1 -1
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: 0.6266
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- - Bleu: 0.2679
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- - Rouge1: 0.5977
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- - Rouge2: 0.3443
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- - Rougel: 0.5959
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  ## Model description
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@@ -52,23 +52,16 @@ The following hyperparameters were used during training:
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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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- | 1.2513 | 1.0 | 2703 | 0.2201 | 0.7112 | 0.5172 | 0.2533 | 0.5148 |
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- | 0.6462 | 2.0 | 5406 | 0.2451 | 0.6569 | 0.5579 | 0.2974 | 0.5553 |
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- | 0.5673 | 3.0 | 8109 | 0.2518 | 0.6499 | 0.5702 | 0.3118 | 0.5677 |
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- | 0.556 | 4.0 | 10812 | 0.2598 | 0.6330 | 0.5829 | 0.3262 | 0.5807 |
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- | 0.4786 | 5.0 | 13515 | 0.2679 | 0.6266 | 0.5977 | 0.3443 | 0.5959 |
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- | 0.4123 | 6.0 | 16218 | 0.2707 | 0.6303 | 0.6044 | 0.3548 | 0.6027 |
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- | 0.3573 | 7.0 | 18921 | 0.2739 | 0.6372 | 0.6108 | 0.3631 | 0.6088 |
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- | 0.3108 | 8.0 | 21624 | 0.2760 | 0.6466 | 0.6130 | 0.3678 | 0.6112 |
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- | 0.2719 | 9.0 | 24327 | 0.2802 | 0.6551 | 0.6178 | 0.3727 | 0.6159 |
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- | 0.2396 | 10.0 | 27030 | 0.2770 | 0.6658 | 0.6173 | 0.3729 | 0.6153 |
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- | 0.2129 | 11.0 | 29733 | 0.6768 | 0.2784 | 0.6188 | 0.3762 | 0.6171 |
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- | 0.191 | 12.0 | 32436 | 0.6870 | 0.2780 | 0.6208 | 0.3781 | 0.6189 |
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- | 0.1733 | 13.0 | 35139 | 0.6967 | 0.2800 | 0.6214 | 0.3799 | 0.6195 |
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- | 0.1593 | 14.0 | 37842 | 0.7063 | 0.2790 | 0.6215 | 0.3799 | 0.6195 |
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- | 0.1478 | 15.0 | 40545 | 0.7139 | 0.2809 | 0.6216 | 0.3804 | 0.6197 |
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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: 0.6607
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+ - Bleu: 0.3968
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+ - Rouge1: 0.6232
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+ - Rouge2: 0.3746
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+ - Rougel: 0.6212
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  ## Model description
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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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+ | 1.2336 | 1.0 | 2679 | 0.7062 | 0.3526 | 0.5198 | 0.2547 | 0.5170 |
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+ | 0.634 | 2.0 | 5358 | 0.6423 | 0.3756 | 0.5739 | 0.3114 | 0.5714 |
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+ | 0.5299 | 3.0 | 8037 | 0.6246 | 0.3877 | 0.5958 | 0.3370 | 0.5935 |
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+ | 0.4492 | 4.0 | 10716 | 0.6246 | 0.3905 | 0.6081 | 0.3526 | 0.6057 |
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+ | 0.3829 | 5.0 | 13395 | 0.6300 | 0.3963 | 0.6145 | 0.3621 | 0.6125 |
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+ | 0.328 | 6.0 | 16074 | 0.6384 | 0.3961 | 0.6213 | 0.3700 | 0.6194 |
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+ | 0.2832 | 7.0 | 18753 | 0.6491 | 0.3999 | 0.6232 | 0.3741 | 0.6209 |
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+ | 0.2453 | 8.0 | 21432 | 0.6607 | 0.3968 | 0.6232 | 0.3746 | 0.6212 |
 
 
 
 
 
 
 
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  ### Framework versions
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