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100M_high_2000_634

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: 3.2973
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- - Accuracy: 0.3949
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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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- | 5.1238 | 0.1076 | 1000 | 5.0474 | 0.2245 |
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- | 4.6101 | 0.2153 | 2000 | 4.5428 | 0.2660 |
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- | 4.327 | 0.3229 | 3000 | 4.2513 | 0.2964 |
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- | 4.18 | 0.4305 | 4000 | 4.1040 | 0.3112 |
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- | 4.0788 | 0.5382 | 5000 | 4.0013 | 0.3209 |
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- | 3.9809 | 0.6458 | 6000 | 3.9289 | 0.3274 |
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- | 3.9432 | 0.7534 | 7000 | 3.8685 | 0.3328 |
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- | 3.8951 | 0.8610 | 8000 | 3.8222 | 0.3374 |
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- | 3.8465 | 0.9687 | 9000 | 3.7847 | 0.3411 |
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- | 3.7776 | 1.0763 | 10000 | 3.7543 | 0.3437 |
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- | 3.7468 | 1.1839 | 11000 | 3.7271 | 0.3463 |
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- | 3.7506 | 1.2916 | 12000 | 3.7040 | 0.3491 |
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- | 3.7237 | 1.3992 | 13000 | 3.6814 | 0.3514 |
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- | 3.7012 | 1.5068 | 14000 | 3.6622 | 0.3531 |
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- | 3.7034 | 1.6145 | 15000 | 3.6405 | 0.3549 |
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- | 3.6725 | 1.7221 | 16000 | 3.6242 | 0.3569 |
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- | 3.672 | 1.8297 | 17000 | 3.6070 | 0.3583 |
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- | 3.6299 | 1.9374 | 18000 | 3.5937 | 0.3599 |
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- | 3.5547 | 2.0450 | 19000 | 3.5826 | 0.3614 |
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- | 3.5597 | 2.1526 | 20000 | 3.5708 | 0.3630 |
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- | 3.5548 | 2.2603 | 21000 | 3.5607 | 0.3637 |
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- | 3.5652 | 2.3679 | 22000 | 3.5529 | 0.3651 |
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- | 3.5598 | 2.4755 | 23000 | 3.5399 | 0.3658 |
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- | 3.5437 | 2.5831 | 24000 | 3.5304 | 0.3672 |
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- | 3.5538 | 2.6908 | 25000 | 3.5202 | 0.3680 |
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- | 3.5305 | 2.7984 | 26000 | 3.5113 | 0.3689 |
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- | 3.5247 | 2.9060 | 27000 | 3.5038 | 0.3698 |
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- | 3.4459 | 3.0137 | 28000 | 3.4984 | 0.3706 |
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- | 3.474 | 3.1213 | 29000 | 3.4933 | 0.3714 |
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- | 3.4539 | 3.2289 | 30000 | 3.4909 | 0.3722 |
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- | 3.4761 | 3.3366 | 31000 | 3.4805 | 0.3729 |
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- | 3.4639 | 3.4442 | 32000 | 3.4724 | 0.3736 |
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- | 3.4517 | 3.5518 | 33000 | 3.4675 | 0.3739 |
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- | 3.4599 | 3.6595 | 34000 | 3.4607 | 0.3744 |
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- | 3.4716 | 3.7671 | 35000 | 3.4529 | 0.3753 |
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- | 3.4683 | 3.8747 | 36000 | 3.4506 | 0.3759 |
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- | 3.4573 | 3.9823 | 37000 | 3.4418 | 0.3767 |
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- | 3.3698 | 4.0900 | 38000 | 3.4448 | 0.3770 |
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- | 3.3879 | 4.1976 | 39000 | 3.4373 | 0.3774 |
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- | 3.3817 | 4.3052 | 40000 | 3.4343 | 0.3781 |
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- | 3.3943 | 4.4129 | 41000 | 3.4277 | 0.3784 |
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- | 3.3975 | 4.5205 | 42000 | 3.4233 | 0.3789 |
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- | 3.3875 | 4.6281 | 43000 | 3.4212 | 0.3793 |
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- | 3.3821 | 4.7358 | 44000 | 3.4130 | 0.3804 |
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- | 3.3768 | 4.8434 | 45000 | 3.4080 | 0.3806 |
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- | 3.3833 | 4.9510 | 46000 | 3.4057 | 0.3807 |
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- | 3.2774 | 5.0587 | 47000 | 3.4080 | 0.3811 |
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- | 3.334 | 5.1663 | 48000 | 3.4050 | 0.3818 |
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- | 3.3145 | 5.2739 | 49000 | 3.4024 | 0.3823 |
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- | 3.3141 | 5.3816 | 50000 | 3.3990 | 0.3824 |
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- | 3.3453 | 5.4892 | 51000 | 3.3912 | 0.3831 |
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- | 3.3352 | 5.5968 | 52000 | 3.3894 | 0.3829 |
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- | 3.3216 | 5.7044 | 53000 | 3.3845 | 0.3838 |
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- | 3.3479 | 5.8121 | 54000 | 3.3777 | 0.3841 |
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- | 3.3476 | 5.9197 | 55000 | 3.3771 | 0.3847 |
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- | 3.2375 | 6.0273 | 56000 | 3.3784 | 0.3848 |
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- | 3.2627 | 6.1350 | 57000 | 3.3782 | 0.3847 |
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- | 3.2627 | 6.2426 | 58000 | 3.3758 | 0.3850 |
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- | 3.2839 | 6.3502 | 59000 | 3.3710 | 0.3857 |
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- | 3.2989 | 6.4579 | 60000 | 3.3687 | 0.3857 |
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- | 3.2743 | 6.5655 | 61000 | 3.3620 | 0.3866 |
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- | 3.2791 | 6.6731 | 62000 | 3.3584 | 0.3868 |
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- | 3.2852 | 6.7808 | 63000 | 3.3554 | 0.3874 |
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- | 3.2907 | 6.8884 | 64000 | 3.3510 | 0.3876 |
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- | 3.2801 | 6.9960 | 65000 | 3.3469 | 0.3881 |
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- | 3.2135 | 7.1036 | 66000 | 3.3548 | 0.3879 |
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- | 3.2265 | 7.2113 | 67000 | 3.3512 | 0.3881 |
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- | 3.2246 | 7.3189 | 68000 | 3.3511 | 0.3881 |
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- | 3.238 | 7.4265 | 69000 | 3.3462 | 0.3888 |
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- | 3.2426 | 7.5342 | 70000 | 3.3393 | 0.3896 |
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- | 3.2285 | 7.6418 | 71000 | 3.3385 | 0.3897 |
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- | 3.2196 | 7.7494 | 72000 | 3.3344 | 0.3901 |
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- | 3.2332 | 7.8571 | 73000 | 3.3292 | 0.3905 |
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- | 3.2324 | 7.9647 | 74000 | 3.3260 | 0.3908 |
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- | 3.166 | 8.0723 | 75000 | 3.3311 | 0.3905 |
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- | 3.1575 | 8.1800 | 76000 | 3.3304 | 0.3909 |
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- | 3.1742 | 8.2876 | 77000 | 3.3261 | 0.3914 |
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- | 3.1689 | 8.3952 | 78000 | 3.3249 | 0.3915 |
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- | 3.1832 | 8.5029 | 79000 | 3.3202 | 0.3919 |
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- | 3.1731 | 8.6105 | 80000 | 3.3172 | 0.3922 |
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- | 3.1745 | 8.7181 | 81000 | 3.3136 | 0.3927 |
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- | 3.2062 | 8.8257 | 82000 | 3.3107 | 0.3930 |
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- | 3.1827 | 8.9334 | 83000 | 3.3073 | 0.3932 |
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- | 3.1252 | 9.0410 | 84000 | 3.3080 | 0.3934 |
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- | 3.1172 | 9.1486 | 85000 | 3.3087 | 0.3936 |
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- | 3.1315 | 9.2563 | 86000 | 3.3066 | 0.3938 |
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- | 3.1489 | 9.3639 | 87000 | 3.3037 | 0.3941 |
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- | 3.1382 | 9.4715 | 88000 | 3.3020 | 0.3944 |
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- | 3.1278 | 9.5792 | 89000 | 3.2999 | 0.3946 |
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- | 3.1205 | 9.6868 | 90000 | 3.2973 | 0.3949 |
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- | 3.1305 | 9.7944 | 91000 | 3.2960 | 0.3950 |
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- | 3.1249 | 9.9021 | 92000 | 3.2941 | 0.3953 |
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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: 3.2968
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+ - Accuracy: 0.3950
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22
  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:-----:|:---------------:|:--------:|
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+ | 5.0898 | 0.1078 | 1000 | 5.0378 | 0.2260 |
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+ | 4.5856 | 0.2156 | 2000 | 4.5164 | 0.2698 |
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+ | 4.318 | 0.3235 | 3000 | 4.2368 | 0.2984 |
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+ | 4.1599 | 0.4313 | 4000 | 4.0911 | 0.3121 |
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+ | 4.0769 | 0.5391 | 5000 | 3.9944 | 0.3214 |
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+ | 3.9652 | 0.6469 | 6000 | 3.9196 | 0.3285 |
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+ | 3.9319 | 0.7547 | 7000 | 3.8620 | 0.3335 |
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+ | 3.8678 | 0.8625 | 8000 | 3.8159 | 0.3378 |
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+ | 3.8659 | 0.9704 | 9000 | 3.7764 | 0.3416 |
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+ | 3.7684 | 1.0782 | 10000 | 3.7473 | 0.3455 |
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+ | 3.7394 | 1.1860 | 11000 | 3.7202 | 0.3477 |
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+ | 3.7237 | 1.2938 | 12000 | 3.6996 | 0.3494 |
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+ | 3.7147 | 1.4016 | 13000 | 3.6778 | 0.3522 |
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+ | 3.6968 | 1.5094 | 14000 | 3.6541 | 0.3542 |
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+ | 3.6812 | 1.6173 | 15000 | 3.6343 | 0.3561 |
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+ | 3.6561 | 1.7251 | 16000 | 3.6196 | 0.3576 |
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+ | 3.6346 | 1.8329 | 17000 | 3.6014 | 0.3591 |
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+ | 3.6447 | 1.9407 | 18000 | 3.5890 | 0.3606 |
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+ | 3.5613 | 2.0485 | 19000 | 3.5791 | 0.3618 |
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+ | 3.5577 | 2.1563 | 20000 | 3.5720 | 0.3629 |
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+ | 3.5463 | 2.2642 | 21000 | 3.5582 | 0.3645 |
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+ | 3.5595 | 2.3720 | 22000 | 3.5470 | 0.3652 |
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+ | 3.5432 | 2.4798 | 23000 | 3.5357 | 0.3663 |
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+ | 3.543 | 2.5876 | 24000 | 3.5278 | 0.3672 |
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+ | 3.5497 | 2.6954 | 25000 | 3.5176 | 0.3683 |
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+ | 3.5322 | 2.8032 | 26000 | 3.5105 | 0.3691 |
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+ | 3.5355 | 2.9111 | 27000 | 3.5018 | 0.3701 |
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+ | 3.4249 | 3.0189 | 28000 | 3.4981 | 0.3708 |
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+ | 3.4491 | 3.1267 | 29000 | 3.4903 | 0.3714 |
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+ | 3.4601 | 3.2345 | 30000 | 3.4878 | 0.3719 |
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+ | 3.4446 | 3.3423 | 31000 | 3.4790 | 0.3729 |
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+ | 3.4568 | 3.4501 | 32000 | 3.4748 | 0.3734 |
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+ | 3.4435 | 3.5580 | 33000 | 3.4657 | 0.3742 |
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+ | 3.4578 | 3.6658 | 34000 | 3.4605 | 0.3746 |
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+ | 3.4416 | 3.7736 | 35000 | 3.4539 | 0.3751 |
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+ | 3.4502 | 3.8814 | 36000 | 3.4471 | 0.3760 |
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+ | 3.4373 | 3.9892 | 37000 | 3.4409 | 0.3765 |
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+ | 3.3767 | 4.0970 | 38000 | 3.4445 | 0.3772 |
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+ | 3.373 | 4.2049 | 39000 | 3.4392 | 0.3776 |
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+ | 3.392 | 4.3127 | 40000 | 3.4344 | 0.3781 |
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+ | 3.3854 | 4.4205 | 41000 | 3.4283 | 0.3784 |
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+ | 3.3821 | 4.5283 | 42000 | 3.4244 | 0.3794 |
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+ | 3.401 | 4.6361 | 43000 | 3.4207 | 0.3796 |
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+ | 3.3665 | 4.7439 | 44000 | 3.4135 | 0.3801 |
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+ | 3.3903 | 4.8518 | 45000 | 3.4105 | 0.3805 |
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+ | 3.3817 | 4.9596 | 46000 | 3.4059 | 0.3811 |
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+ | 3.3072 | 5.0674 | 47000 | 3.4111 | 0.3811 |
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+ | 3.3098 | 5.1752 | 48000 | 3.4069 | 0.3814 |
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+ | 3.3077 | 5.2830 | 49000 | 3.4026 | 0.3818 |
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+ | 3.3346 | 5.3908 | 50000 | 3.3976 | 0.3826 |
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+ | 3.3158 | 5.4987 | 51000 | 3.3934 | 0.3828 |
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+ | 3.3372 | 5.6065 | 52000 | 3.3891 | 0.3833 |
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+ | 3.3439 | 5.7143 | 53000 | 3.3844 | 0.3838 |
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+ | 3.3264 | 5.8221 | 54000 | 3.3800 | 0.3839 |
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+ | 3.3255 | 5.9299 | 55000 | 3.3736 | 0.3847 |
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+ | 3.2574 | 6.0377 | 56000 | 3.3796 | 0.3845 |
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+ | 3.2472 | 6.1456 | 57000 | 3.3794 | 0.3844 |
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+ | 3.2498 | 6.2534 | 58000 | 3.3766 | 0.3850 |
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+ | 3.2837 | 6.3612 | 59000 | 3.3718 | 0.3855 |
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+ | 3.2842 | 6.4690 | 60000 | 3.3680 | 0.3860 |
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+ | 3.2768 | 6.5768 | 61000 | 3.3646 | 0.3863 |
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+ | 3.2687 | 6.6846 | 62000 | 3.3587 | 0.3870 |
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+ | 3.2747 | 6.7925 | 63000 | 3.3571 | 0.3871 |
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+ | 3.2918 | 6.9003 | 64000 | 3.3522 | 0.3878 |
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+ | 3.1963 | 7.0081 | 65000 | 3.3556 | 0.3876 |
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+ | 3.215 | 7.1159 | 66000 | 3.3556 | 0.3878 |
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+ | 3.2174 | 7.2237 | 67000 | 3.3524 | 0.3881 |
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+ | 3.2221 | 7.3315 | 68000 | 3.3498 | 0.3886 |
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+ | 3.2419 | 7.4394 | 69000 | 3.3461 | 0.3886 |
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+ | 3.2273 | 7.5472 | 70000 | 3.3428 | 0.3892 |
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+ | 3.2237 | 7.6550 | 71000 | 3.3384 | 0.3895 |
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+ | 3.2369 | 7.7628 | 72000 | 3.3330 | 0.3898 |
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+ | 3.2185 | 7.8706 | 73000 | 3.3296 | 0.3904 |
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+ | 3.2295 | 7.9784 | 74000 | 3.3277 | 0.3908 |
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+ | 3.1578 | 8.0863 | 75000 | 3.3346 | 0.3905 |
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+ | 3.1652 | 8.1941 | 76000 | 3.3307 | 0.3909 |
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+ | 3.1765 | 8.3019 | 77000 | 3.3292 | 0.3909 |
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+ | 3.1669 | 8.4097 | 78000 | 3.3254 | 0.3914 |
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+ | 3.181 | 8.5175 | 79000 | 3.3227 | 0.3917 |
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+ | 3.1792 | 8.6253 | 80000 | 3.3198 | 0.3922 |
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+ | 3.1909 | 8.7332 | 81000 | 3.3156 | 0.3923 |
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+ | 3.1764 | 8.8410 | 82000 | 3.3124 | 0.3929 |
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+ | 3.1907 | 8.9488 | 83000 | 3.3093 | 0.3932 |
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+ | 3.1206 | 9.0566 | 84000 | 3.3131 | 0.3930 |
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+ | 3.1212 | 9.1644 | 85000 | 3.3112 | 0.3933 |
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+ | 3.1316 | 9.2722 | 86000 | 3.3090 | 0.3935 |
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+ | 3.1184 | 9.3801 | 87000 | 3.3082 | 0.3937 |
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+ | 3.128 | 9.4879 | 88000 | 3.3045 | 0.3942 |
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+ | 3.1446 | 9.5957 | 89000 | 3.3022 | 0.3943 |
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+ | 3.1292 | 9.7035 | 90000 | 3.3002 | 0.3946 |
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+ | 3.1313 | 9.8113 | 91000 | 3.2983 | 0.3948 |
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+ | 3.1045 | 9.9191 | 92000 | 3.2968 | 0.3950 |
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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 sha256:2f67d5b19f0af512fc6950cff4951ce73d8239bf55530668f73d865dc3f90e20
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  size 503128704
 
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  version https://git-lfs.github.com/spec/v1
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+ oid sha256:5a03b9d1afbc8ca8bce06ac6bafde4fcf495ea9e2f43a7d06cf676782f0d5d78
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  size 503128704