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Safetensors
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Mojiz-DPO

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  1. README.md +27 -17
  2. adapter_model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -17,14 +17,14 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [ahmedabdelwahed/Mojiz-sft](https://huggingface.co/ahmedabdelwahed/Mojiz-sft) on the None dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.0000
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- - Rewards/chosen: 16.5213
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- - Rewards/rejected: -7.9440
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  - Rewards/accuracies: 1.0
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- - Rewards/margins: 24.4653
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- - Logps/rejected: -86.9274
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- - Logps/chosen: -293.2704
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- - Logits/rejected: -11.2915
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- - Logits/chosen: -12.2516
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  ## Model description
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@@ -50,22 +50,32 @@ 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: 150
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- - training_steps: 1000
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
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  |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
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  | 0.0017 | 0.41 | 100 | 0.0000 | 9.9359 | -3.7597 | 1.0 | 13.6956 | -78.5589 | -306.4413 | -11.4127 | -12.4541 |
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- | 0.0002 | 0.82 | 200 | 0.0000 | 14.1969 | -5.8004 | 1.0 | 19.9973 | -82.6403 | -297.9192 | -11.3000 | -12.2682 |
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- | 0.0037 | 1.22 | 300 | 0.0000 | 14.8615 | -6.7633 | 1.0 | 21.6248 | -84.5661 | -296.5901 | -11.2673 | -12.2269 |
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- | 0.0 | 1.63 | 400 | 0.0000 | 15.4935 | -7.6471 | 1.0 | 23.1406 | -86.3337 | -295.3261 | -11.2271 | -12.1591 |
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- | 0.0 | 2.04 | 500 | 0.0000 | 15.8634 | -7.8871 | 1.0 | 23.7505 | -86.8136 | -294.5863 | -11.2316 | -12.1672 |
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- | 0.0 | 2.45 | 600 | 0.0000 | 16.1624 | -7.8756 | 1.0 | 24.0380 | -86.7906 | -293.9882 | -11.2578 | -12.2052 |
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- | 0.0 | 2.86 | 700 | 0.0000 | 16.1247 | -8.2229 | 1.0 | 24.3476 | -87.4853 | -294.0637 | -11.2414 | -12.1705 |
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- | 0.0 | 3.27 | 800 | 0.0000 | 16.4219 | -7.9771 | 1.0 | 24.3989 | -86.9936 | -293.4693 | -11.2814 | -12.2344 |
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- | 0.0 | 3.67 | 900 | 0.0000 | 16.4248 | -7.9873 | 1.0 | 24.4122 | -87.0141 | -293.4634 | -11.2812 | -12.2342 |
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- | 0.0 | 4.08 | 1000 | 0.0000 | 16.5213 | -7.9440 | 1.0 | 24.4653 | -86.9274 | -293.2704 | -11.2915 | -12.2516 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [ahmedabdelwahed/Mojiz-sft](https://huggingface.co/ahmedabdelwahed/Mojiz-sft) on the None dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.0000
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+ - Rewards/chosen: 17.3685
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+ - Rewards/rejected: -9.0879
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  - Rewards/accuracies: 1.0
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+ - Rewards/margins: 26.4564
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+ - Logps/rejected: -89.2152
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+ - Logps/chosen: -291.5760
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+ - Logits/rejected: -11.3625
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+ - Logits/chosen: -12.3502
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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: 150
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+ - training_steps: 2000
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
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  |:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
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  | 0.0017 | 0.41 | 100 | 0.0000 | 9.9359 | -3.7597 | 1.0 | 13.6956 | -78.5589 | -306.4413 | -11.4127 | -12.4541 |
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+ | 0.0002 | 0.82 | 200 | 0.0000 | 14.2220 | -5.8111 | 1.0 | 20.0331 | -82.6616 | -297.8690 | -11.3000 | -12.2683 |
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+ | 0.0036 | 1.22 | 300 | 0.0000 | 14.9129 | -6.8369 | 1.0 | 21.7499 | -84.7133 | -296.4872 | -11.2647 | -12.2239 |
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+ | 0.0 | 1.63 | 400 | 0.0000 | 15.5788 | -7.9152 | 1.0 | 23.4939 | -86.8698 | -295.1555 | -11.2175 | -12.1437 |
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+ | 0.0 | 2.04 | 500 | 0.0000 | 15.9537 | -8.1483 | 1.0 | 24.1020 | -87.3360 | -294.4057 | -11.2256 | -12.1568 |
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+ | 0.0 | 2.45 | 600 | 0.0000 | 16.3724 | -8.1224 | 1.0 | 24.4948 | -87.2842 | -293.5682 | -11.2611 | -12.2092 |
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+ | 0.0 | 2.86 | 700 | 0.0000 | 16.2464 | -8.7026 | 1.0 | 24.9490 | -88.4446 | -293.8203 | -11.2351 | -12.1506 |
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+ | 0.0 | 3.27 | 800 | 0.0000 | 17.0144 | -7.9818 | 1.0 | 24.9962 | -87.0030 | -292.2843 | -11.3359 | -12.3118 |
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+ | 0.0 | 3.67 | 900 | 0.0000 | 17.0212 | -8.0028 | 1.0 | 25.0241 | -87.0451 | -292.2705 | -11.3356 | -12.3114 |
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+ | 0.0 | 4.08 | 1000 | 0.0000 | 17.1508 | -8.0673 | 1.0 | 25.2182 | -87.1741 | -292.0114 | -11.3467 | -12.3293 |
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+ | 0.0 | 4.49 | 1100 | 0.0000 | 17.1035 | -8.6586 | 1.0 | 25.7621 | -88.3567 | -292.1060 | -11.3427 | -12.3196 |
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+ | 0.0 | 4.9 | 1200 | 0.0000 | 17.1191 | -8.6910 | 1.0 | 25.8101 | -88.4214 | -292.0748 | -11.3428 | -12.3192 |
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+ | 0.0 | 5.31 | 1300 | 0.0000 | 17.2084 | -8.9388 | 1.0 | 26.1472 | -88.9170 | -291.8962 | -11.3530 | -12.3370 |
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+ | 0.0 | 5.71 | 1400 | 0.0000 | 17.2160 | -9.1194 | 1.0 | 26.3354 | -89.2783 | -291.8811 | -11.3506 | -12.3312 |
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+ | 0.0 | 6.12 | 1500 | 0.0000 | 17.2326 | -9.1376 | 1.0 | 26.3702 | -89.3146 | -291.8478 | -11.3494 | -12.3291 |
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+ | 0.0002 | 6.53 | 1600 | 0.0000 | 17.2830 | -9.1192 | 1.0 | 26.4022 | -89.2778 | -291.7470 | -11.3555 | -12.3384 |
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+ | 0.0 | 6.94 | 1700 | 0.0000 | 17.3062 | -9.1044 | 1.0 | 26.4107 | -89.2482 | -291.7006 | -11.3582 | -12.3429 |
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+ | 0.0 | 7.35 | 1800 | 0.0000 | 17.3229 | -9.1143 | 1.0 | 26.4372 | -89.2681 | -291.6673 | -11.3586 | -12.3435 |
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+ | 0.0 | 7.76 | 1900 | 0.0000 | 17.3411 | -9.1107 | 1.0 | 26.4518 | -89.2609 | -291.6309 | -11.3600 | -12.3457 |
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+ | 0.0 | 8.16 | 2000 | 0.0000 | 17.3685 | -9.0879 | 1.0 | 26.4564 | -89.2152 | -291.5760 | -11.3625 | -12.3502 |
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  ### Framework versions
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