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100M_high_2000_8397

Text Generation
Transformers
Safetensors
gpt2
Generated from Trainer
text-generation-inference
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  1. README.md +94 -94
  2. model.safetensors +1 -1
README.md CHANGED
@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 3.3019
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- - Accuracy: 0.3944
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  ## Model description
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@@ -50,98 +50,98 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:-----:|:---------------:|:--------:|
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- | 5.0633 | 0.1076 | 1000 | 4.9965 | 0.2292 |
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- | 4.579 | 0.2153 | 2000 | 4.5043 | 0.2712 |
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- | 4.322 | 0.3229 | 3000 | 4.2267 | 0.2992 |
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- | 4.1439 | 0.4305 | 4000 | 4.0925 | 0.3122 |
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- | 4.043 | 0.5382 | 5000 | 3.9926 | 0.3214 |
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- | 3.9759 | 0.6458 | 6000 | 3.9196 | 0.3283 |
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- | 3.922 | 0.7534 | 7000 | 3.8611 | 0.3334 |
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- | 3.8731 | 0.8610 | 8000 | 3.8146 | 0.3380 |
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- | 3.8405 | 0.9687 | 9000 | 3.7791 | 0.3417 |
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- | 3.7655 | 1.0763 | 10000 | 3.7489 | 0.3451 |
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- | 3.7441 | 1.1839 | 11000 | 3.7200 | 0.3471 |
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- | 3.7293 | 1.2916 | 12000 | 3.6987 | 0.3496 |
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- | 3.7029 | 1.3992 | 13000 | 3.6745 | 0.3523 |
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- | 3.6962 | 1.5068 | 14000 | 3.6557 | 0.3536 |
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- | 3.6601 | 1.6145 | 15000 | 3.6367 | 0.3556 |
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- | 3.6579 | 1.7221 | 16000 | 3.6183 | 0.3572 |
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- | 3.6582 | 1.8297 | 17000 | 3.6050 | 0.3590 |
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- | 3.6427 | 1.9374 | 18000 | 3.5893 | 0.3606 |
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- | 3.56 | 2.0450 | 19000 | 3.5785 | 0.3617 |
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- | 3.5527 | 2.1526 | 20000 | 3.5706 | 0.3627 |
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- | 3.5487 | 2.2603 | 21000 | 3.5602 | 0.3639 |
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- | 3.5664 | 2.3679 | 22000 | 3.5475 | 0.3650 |
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- | 3.5464 | 2.4755 | 23000 | 3.5418 | 0.3655 |
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- | 3.5619 | 2.5831 | 24000 | 3.5326 | 0.3666 |
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- | 3.5487 | 2.6908 | 25000 | 3.5214 | 0.3681 |
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- | 3.5277 | 2.7984 | 26000 | 3.5125 | 0.3686 |
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- | 3.5346 | 2.9060 | 27000 | 3.5038 | 0.3695 |
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- | 3.4461 | 3.0137 | 28000 | 3.4977 | 0.3707 |
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- | 3.4491 | 3.1213 | 29000 | 3.4946 | 0.3712 |
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- | 3.4684 | 3.2289 | 30000 | 3.4922 | 0.3713 |
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- | 3.4662 | 3.3366 | 31000 | 3.4845 | 0.3721 |
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- | 3.4454 | 3.4442 | 32000 | 3.4765 | 0.3731 |
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- | 3.4605 | 3.5518 | 33000 | 3.4697 | 0.3741 |
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- | 3.4428 | 3.6595 | 34000 | 3.4640 | 0.3745 |
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- | 3.458 | 3.7671 | 35000 | 3.4591 | 0.3749 |
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- | 3.4501 | 3.8747 | 36000 | 3.4519 | 0.3758 |
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- | 3.4582 | 3.9823 | 37000 | 3.4467 | 0.3758 |
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- | 3.3691 | 4.0900 | 38000 | 3.4484 | 0.3766 |
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- | 3.3847 | 4.1976 | 39000 | 3.4444 | 0.3769 |
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- | 3.3714 | 4.3052 | 40000 | 3.4397 | 0.3772 |
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- | 3.3768 | 4.4129 | 41000 | 3.4378 | 0.3780 |
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- | 3.393 | 4.5205 | 42000 | 3.4299 | 0.3785 |
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- | 3.3915 | 4.6281 | 43000 | 3.4237 | 0.3790 |
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- | 3.3875 | 4.7358 | 44000 | 3.4192 | 0.3795 |
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- | 3.4045 | 4.8434 | 45000 | 3.4141 | 0.3801 |
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- | 3.3761 | 4.9510 | 46000 | 3.4095 | 0.3805 |
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- | 3.3004 | 5.0587 | 47000 | 3.4123 | 0.3809 |
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- | 3.3289 | 5.1663 | 48000 | 3.4115 | 0.3815 |
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- | 3.3151 | 5.2739 | 49000 | 3.4057 | 0.3817 |
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- | 3.3528 | 5.3816 | 50000 | 3.4026 | 0.3818 |
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- | 3.3271 | 5.4892 | 51000 | 3.3986 | 0.3823 |
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- | 3.3457 | 5.5968 | 52000 | 3.3944 | 0.3825 |
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- | 3.3489 | 5.7044 | 53000 | 3.3893 | 0.3832 |
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- | 3.3353 | 5.8121 | 54000 | 3.3865 | 0.3837 |
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- | 3.3306 | 5.9197 | 55000 | 3.3798 | 0.3840 |
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- | 3.2266 | 6.0273 | 56000 | 3.3825 | 0.3844 |
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- | 3.2555 | 6.1350 | 57000 | 3.3847 | 0.3842 |
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- | 3.2849 | 6.2426 | 58000 | 3.3810 | 0.3847 |
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- | 3.2801 | 6.3502 | 59000 | 3.3766 | 0.3852 |
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- | 3.2773 | 6.4579 | 60000 | 3.3726 | 0.3854 |
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- | 3.3014 | 6.5655 | 61000 | 3.3667 | 0.3860 |
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- | 3.2774 | 6.6731 | 62000 | 3.3637 | 0.3862 |
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- | 3.2826 | 6.7808 | 63000 | 3.3598 | 0.3868 |
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- | 3.2734 | 6.8884 | 64000 | 3.3552 | 0.3873 |
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- | 3.2676 | 6.9960 | 65000 | 3.3523 | 0.3876 |
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- | 3.2141 | 7.1036 | 66000 | 3.3576 | 0.3874 |
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- | 3.2343 | 7.2113 | 67000 | 3.3561 | 0.3876 |
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- | 3.2277 | 7.3189 | 68000 | 3.3523 | 0.3881 |
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- | 3.236 | 7.4265 | 69000 | 3.3499 | 0.3886 |
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- | 3.2201 | 7.5342 | 70000 | 3.3478 | 0.3887 |
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- | 3.2337 | 7.6418 | 71000 | 3.3436 | 0.3891 |
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- | 3.2174 | 7.7494 | 72000 | 3.3376 | 0.3896 |
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- | 3.2182 | 7.8571 | 73000 | 3.3348 | 0.3899 |
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- | 3.2393 | 7.9647 | 74000 | 3.3314 | 0.3900 |
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- | 3.1517 | 8.0723 | 75000 | 3.3365 | 0.3900 |
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- | 3.1824 | 8.1800 | 76000 | 3.3342 | 0.3904 |
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- | 3.1814 | 8.2876 | 77000 | 3.3317 | 0.3906 |
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- | 3.1945 | 8.3952 | 78000 | 3.3278 | 0.3912 |
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- | 3.1847 | 8.5029 | 79000 | 3.3260 | 0.3915 |
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- | 3.1648 | 8.6105 | 80000 | 3.3222 | 0.3918 |
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- | 3.179 | 8.7181 | 81000 | 3.3188 | 0.3920 |
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- | 3.1809 | 8.8257 | 82000 | 3.3150 | 0.3926 |
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- | 3.1939 | 8.9334 | 83000 | 3.3116 | 0.3928 |
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- | 3.1185 | 9.0410 | 84000 | 3.3150 | 0.3928 |
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- | 3.1242 | 9.1486 | 85000 | 3.3141 | 0.3930 |
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- | 3.1324 | 9.2563 | 86000 | 3.3112 | 0.3933 |
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- | 3.1224 | 9.3639 | 87000 | 3.3099 | 0.3935 |
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- | 3.1341 | 9.4715 | 88000 | 3.3078 | 0.3937 |
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- | 3.1354 | 9.5792 | 89000 | 3.3048 | 0.3941 |
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- | 3.1262 | 9.6868 | 90000 | 3.3019 | 0.3944 |
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- | 3.129 | 9.7944 | 91000 | 3.3006 | 0.3946 |
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- | 3.1392 | 9.9021 | 92000 | 3.2992 | 0.3947 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 3.3012
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+ - Accuracy: 0.3942
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:-----:|:---------------:|:--------:|
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+ | 5.1266 | 0.1078 | 1000 | 5.0416 | 0.2255 |
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+ | 4.6194 | 0.2156 | 2000 | 4.5361 | 0.2671 |
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+ | 4.3296 | 0.3235 | 3000 | 4.2696 | 0.2954 |
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+ | 4.1751 | 0.4313 | 4000 | 4.0999 | 0.3114 |
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+ | 4.0618 | 0.5391 | 5000 | 4.0008 | 0.3203 |
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+ | 4.0077 | 0.6469 | 6000 | 3.9325 | 0.3263 |
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+ | 3.9306 | 0.7547 | 7000 | 3.8742 | 0.3323 |
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+ | 3.8636 | 0.8625 | 8000 | 3.8250 | 0.3369 |
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+ | 3.8653 | 0.9704 | 9000 | 3.7883 | 0.3401 |
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+ | 3.7721 | 1.0782 | 10000 | 3.7573 | 0.3433 |
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+ | 3.7783 | 1.1860 | 11000 | 3.7309 | 0.3463 |
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+ | 3.7384 | 1.2938 | 12000 | 3.7029 | 0.3486 |
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+ | 3.7152 | 1.4016 | 13000 | 3.6820 | 0.3510 |
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+ | 3.7106 | 1.5094 | 14000 | 3.6608 | 0.3530 |
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+ | 3.673 | 1.6173 | 15000 | 3.6430 | 0.3548 |
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+ | 3.6719 | 1.7251 | 16000 | 3.6251 | 0.3568 |
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+ | 3.6449 | 1.8329 | 17000 | 3.6107 | 0.3580 |
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+ | 3.6395 | 1.9407 | 18000 | 3.5955 | 0.3591 |
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+ | 3.5784 | 2.0485 | 19000 | 3.5867 | 0.3613 |
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+ | 3.5816 | 2.1563 | 20000 | 3.5776 | 0.3616 |
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+ | 3.5716 | 2.2642 | 21000 | 3.5651 | 0.3632 |
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+ | 3.5795 | 2.3720 | 22000 | 3.5569 | 0.3641 |
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+ | 3.5451 | 2.4798 | 23000 | 3.5442 | 0.3651 |
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+ | 3.5389 | 2.5876 | 24000 | 3.5345 | 0.3665 |
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+ | 3.5351 | 2.6954 | 25000 | 3.5261 | 0.3669 |
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+ | 3.5397 | 2.8032 | 26000 | 3.5164 | 0.3679 |
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+ | 3.5532 | 2.9111 | 27000 | 3.5089 | 0.3690 |
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+ | 3.4533 | 3.0189 | 28000 | 3.5048 | 0.3695 |
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+ | 3.4393 | 3.1267 | 29000 | 3.5027 | 0.3705 |
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+ | 3.4587 | 3.2345 | 30000 | 3.4946 | 0.3711 |
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+ | 3.4655 | 3.3423 | 31000 | 3.4889 | 0.3713 |
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+ | 3.4673 | 3.4501 | 32000 | 3.4800 | 0.3726 |
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+ | 3.469 | 3.5580 | 33000 | 3.4780 | 0.3731 |
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+ | 3.4678 | 3.6658 | 34000 | 3.4688 | 0.3732 |
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+ | 3.4686 | 3.7736 | 35000 | 3.4623 | 0.3744 |
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+ | 3.4592 | 3.8814 | 36000 | 3.4562 | 0.3747 |
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+ | 3.4572 | 3.9892 | 37000 | 3.4497 | 0.3755 |
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+ | 3.3731 | 4.0970 | 38000 | 3.4552 | 0.3757 |
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+ | 3.3721 | 4.2049 | 39000 | 3.4490 | 0.3767 |
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+ | 3.3974 | 4.3127 | 40000 | 3.4448 | 0.3770 |
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+ | 3.4023 | 4.4205 | 41000 | 3.4379 | 0.3774 |
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+ | 3.3948 | 4.5283 | 42000 | 3.4337 | 0.3780 |
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+ | 3.4056 | 4.6361 | 43000 | 3.4286 | 0.3781 |
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+ | 3.397 | 4.7439 | 44000 | 3.4248 | 0.3787 |
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+ | 3.4165 | 4.8518 | 45000 | 3.4190 | 0.3796 |
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+ | 3.3811 | 4.9596 | 46000 | 3.4153 | 0.3800 |
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+ | 3.3247 | 5.0674 | 47000 | 3.4145 | 0.3802 |
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+ | 3.323 | 5.1752 | 48000 | 3.4155 | 0.3807 |
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+ | 3.3547 | 5.2830 | 49000 | 3.4113 | 0.3808 |
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+ | 3.3508 | 5.3908 | 50000 | 3.4057 | 0.3814 |
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+ | 3.3525 | 5.4987 | 51000 | 3.4021 | 0.3817 |
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+ | 3.3267 | 5.6065 | 52000 | 3.3966 | 0.3820 |
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+ | 3.3419 | 5.7143 | 53000 | 3.3925 | 0.3826 |
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+ | 3.3404 | 5.8221 | 54000 | 3.3886 | 0.3830 |
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+ | 3.3433 | 5.9299 | 55000 | 3.3859 | 0.3834 |
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+ | 3.245 | 6.0377 | 56000 | 3.3885 | 0.3834 |
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+ | 3.2666 | 6.1456 | 57000 | 3.3866 | 0.3837 |
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+ | 3.2856 | 6.2534 | 58000 | 3.3833 | 0.3841 |
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+ | 3.2984 | 6.3612 | 59000 | 3.3796 | 0.3844 |
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+ | 3.2985 | 6.4690 | 60000 | 3.3764 | 0.3851 |
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+ | 3.2917 | 6.5768 | 61000 | 3.3715 | 0.3854 |
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+ | 3.3085 | 6.6846 | 62000 | 3.3664 | 0.3858 |
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+ | 3.287 | 6.7925 | 63000 | 3.3639 | 0.3863 |
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+ | 3.2978 | 6.9003 | 64000 | 3.3586 | 0.3868 |
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+ | 3.1929 | 7.0081 | 65000 | 3.3601 | 0.3868 |
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+ | 3.2332 | 7.1159 | 66000 | 3.3624 | 0.3869 |
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+ | 3.2376 | 7.2237 | 67000 | 3.3603 | 0.3872 |
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+ | 3.2385 | 7.3315 | 68000 | 3.3575 | 0.3874 |
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+ | 3.2295 | 7.4394 | 69000 | 3.3512 | 0.3878 |
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+ | 3.2336 | 7.5472 | 70000 | 3.3498 | 0.3880 |
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+ | 3.2609 | 7.6550 | 71000 | 3.3443 | 0.3888 |
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+ | 3.2596 | 7.7628 | 72000 | 3.3419 | 0.3890 |
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+ | 3.2395 | 7.8706 | 73000 | 3.3371 | 0.3893 |
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+ | 3.2613 | 7.9784 | 74000 | 3.3327 | 0.3899 |
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+ | 3.1658 | 8.0863 | 75000 | 3.3381 | 0.3898 |
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+ | 3.1677 | 8.1941 | 76000 | 3.3371 | 0.3899 |
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+ | 3.1848 | 8.3019 | 77000 | 3.3346 | 0.3901 |
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+ | 3.1791 | 8.4097 | 78000 | 3.3315 | 0.3905 |
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+ | 3.1914 | 8.5175 | 79000 | 3.3273 | 0.3907 |
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+ | 3.2046 | 8.6253 | 80000 | 3.3241 | 0.3914 |
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+ | 3.1984 | 8.7332 | 81000 | 3.3215 | 0.3917 |
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+ | 3.194 | 8.8410 | 82000 | 3.3170 | 0.3920 |
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+ | 3.1764 | 8.9488 | 83000 | 3.3141 | 0.3923 |
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+ | 3.1378 | 9.0566 | 84000 | 3.3158 | 0.3925 |
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+ | 3.1297 | 9.1644 | 85000 | 3.3160 | 0.3924 |
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+ | 3.1542 | 9.2722 | 86000 | 3.3140 | 0.3929 |
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+ | 3.1329 | 9.3801 | 87000 | 3.3117 | 0.3930 |
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+ | 3.1403 | 9.4879 | 88000 | 3.3090 | 0.3934 |
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+ | 3.1185 | 9.5957 | 89000 | 3.3069 | 0.3935 |
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+ | 3.1479 | 9.7035 | 90000 | 3.3046 | 0.3939 |
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+ | 3.1363 | 9.8113 | 91000 | 3.3026 | 0.3941 |
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+ | 3.1311 | 9.9191 | 92000 | 3.3012 | 0.3942 |
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  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
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  version https://git-lfs.github.com/spec/v1
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- oid sha256:f54a011dc0092c2b0c24f2b0786d6695f7f7e7d5b350c98eb3c818a19c45f070
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  size 503128704
 
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  version https://git-lfs.github.com/spec/v1
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+ oid sha256:6065eaa8e167d9fbfdaf54b68672da4e6c9a1859ee1b662371190c550592f129
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  size 503128704