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res_nw_yem

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: 0.4720
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- - Bleu: 0.2297
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- - Rouge1: 0.5777
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- - Rouge2: 0.3341
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- - Rougel: 0.5758
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  ## Model description
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@@ -52,24 +52,19 @@ 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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- | 7.8314 | 1.0 | 153 | 0.0104 | 2.3597 | 0.0983 | 0.0018 | 0.0964 |
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- | 0.9995 | 2.0 | 306 | 0.1161 | 0.5538 | 0.4736 | 0.1854 | 0.4728 |
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- | 0.4848 | 3.0 | 459 | 0.1472 | 0.5034 | 0.5008 | 0.2174 | 0.5002 |
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- | 0.3823 | 4.0 | 612 | 0.1912 | 0.4827 | 0.5331 | 0.2744 | 0.5314 |
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- | 0.293 | 5.0 | 765 | 0.2096 | 0.4732 | 0.5619 | 0.3099 | 0.5587 |
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- | 0.2239 | 6.0 | 918 | 0.2297 | 0.4720 | 0.5777 | 0.3341 | 0.5758 |
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- | 0.1766 | 7.0 | 1071 | 0.2302 | 0.4737 | 0.5885 | 0.3468 | 0.5872 |
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- | 0.1434 | 8.0 | 1224 | 0.2451 | 0.4758 | 0.5938 | 0.3648 | 0.5903 |
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- | 0.1202 | 9.0 | 1377 | 0.2509 | 0.4828 | 0.6047 | 0.3683 | 0.6015 |
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- | 0.1042 | 10.0 | 1530 | 0.2439 | 0.4852 | 0.5980 | 0.3704 | 0.5951 |
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- | 0.0955 | 11.0 | 1683 | 0.2560 | 0.4885 | 0.6116 | 0.3795 | 0.6086 |
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- | 0.0875 | 12.0 | 1836 | 0.4914 | 0.2551 | 0.6098 | 0.3802 | 0.6056 |
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- | 0.0825 | 13.0 | 1989 | 0.4981 | 0.2627 | 0.6145 | 0.3872 | 0.6108 |
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- | 0.0787 | 14.0 | 2142 | 0.5005 | 0.2590 | 0.6138 | 0.3797 | 0.6101 |
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- | 0.0757 | 15.0 | 2295 | 0.5020 | 0.2632 | 0.6171 | 0.3850 | 0.6141 |
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- | 0.074 | 16.0 | 2448 | 0.5049 | 0.2594 | 0.6161 | 0.3829 | 0.6125 |
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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: 0.4789
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+ - Bleu: 0.4179
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+ - Rouge1: 0.6343
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+ - Rouge2: 0.3810
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+ - Rougel: 0.6307
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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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+ | 7.4125 | 1.0 | 153 | 2.3319 | 0.0135 | 0.4043 | 0.1765 | 0.4039 |
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+ | 1.0077 | 2.0 | 306 | 0.5519 | 0.3376 | 0.4747 | 0.1839 | 0.4733 |
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+ | 0.483 | 3.0 | 459 | 0.4973 | 0.3582 | 0.5145 | 0.2200 | 0.5135 |
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+ | 0.3795 | 4.0 | 612 | 0.4739 | 0.3717 | 0.5397 | 0.2524 | 0.5378 |
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+ | 0.2901 | 5.0 | 765 | 0.4691 | 0.3795 | 0.5710 | 0.2927 | 0.5677 |
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+ | 0.2239 | 6.0 | 918 | 0.4655 | 0.3947 | 0.5909 | 0.3232 | 0.5882 |
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+ | 0.1763 | 7.0 | 1071 | 0.4673 | 0.4011 | 0.6047 | 0.3378 | 0.6019 |
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+ | 0.1429 | 8.0 | 1224 | 0.4666 | 0.4085 | 0.6200 | 0.3652 | 0.6168 |
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+ | 0.1206 | 9.0 | 1377 | 0.4765 | 0.4130 | 0.6230 | 0.3707 | 0.6208 |
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+ | 0.1052 | 10.0 | 1530 | 0.4759 | 0.4148 | 0.6233 | 0.3762 | 0.6205 |
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+ | 0.0955 | 11.0 | 1683 | 0.4789 | 0.4179 | 0.6343 | 0.3810 | 0.6307 |
 
 
 
 
 
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  ### Framework versions
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