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100M_low_100_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: 3.3066
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- - Accuracy: 0.3939
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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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- | 5.0941 | 0.1076 | 1000 | 5.0244 | 0.2268 |
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- | 4.5795 | 0.2153 | 2000 | 4.5077 | 0.2709 |
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- | 4.3173 | 0.3229 | 3000 | 4.2433 | 0.2982 |
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- | 4.1689 | 0.4305 | 4000 | 4.0885 | 0.3122 |
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- | 4.0569 | 0.5382 | 5000 | 3.9963 | 0.3208 |
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- | 4.0125 | 0.6458 | 6000 | 3.9253 | 0.3270 |
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- | 3.9257 | 0.7534 | 7000 | 3.8647 | 0.3327 |
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- | 3.8987 | 0.8610 | 8000 | 3.8250 | 0.3365 |
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- | 3.837 | 0.9687 | 9000 | 3.7822 | 0.3404 |
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- | 3.7725 | 1.0763 | 10000 | 3.7540 | 0.3439 |
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- | 3.7577 | 1.1839 | 11000 | 3.7283 | 0.3465 |
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- | 3.7502 | 1.2916 | 12000 | 3.7033 | 0.3485 |
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- | 3.7256 | 1.3992 | 13000 | 3.6785 | 0.3510 |
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- | 3.7026 | 1.5068 | 14000 | 3.6603 | 0.3528 |
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- | 3.6954 | 1.6145 | 15000 | 3.6429 | 0.3546 |
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- | 3.6735 | 1.7221 | 16000 | 3.6250 | 0.3565 |
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- | 3.6405 | 1.8297 | 17000 | 3.6095 | 0.3582 |
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- | 3.6439 | 1.9374 | 18000 | 3.5955 | 0.3589 |
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- | 3.5585 | 2.0450 | 19000 | 3.5856 | 0.3610 |
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- | 3.5596 | 2.1526 | 20000 | 3.5780 | 0.3617 |
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- | 3.5619 | 2.2603 | 21000 | 3.5658 | 0.3626 |
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- | 3.5593 | 2.3679 | 22000 | 3.5528 | 0.3641 |
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- | 3.5547 | 2.4755 | 23000 | 3.5428 | 0.3651 |
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- | 3.5571 | 2.5831 | 24000 | 3.5348 | 0.3657 |
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- | 3.5501 | 2.6908 | 25000 | 3.5256 | 0.3671 |
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- | 3.5323 | 2.7984 | 26000 | 3.5175 | 0.3677 |
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- | 3.536 | 2.9060 | 27000 | 3.5098 | 0.3692 |
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- | 3.4438 | 3.0137 | 28000 | 3.5057 | 0.3695 |
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- | 3.4492 | 3.1213 | 29000 | 3.5004 | 0.3698 |
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- | 3.4644 | 3.2289 | 30000 | 3.4972 | 0.3709 |
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- | 3.4772 | 3.3366 | 31000 | 3.4864 | 0.3716 |
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- | 3.4697 | 3.4442 | 32000 | 3.4790 | 0.3730 |
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- | 3.4765 | 3.5518 | 33000 | 3.4730 | 0.3731 |
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- | 3.458 | 3.6595 | 34000 | 3.4676 | 0.3739 |
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- | 3.4454 | 3.7671 | 35000 | 3.4650 | 0.3740 |
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- | 3.4562 | 3.8747 | 36000 | 3.4544 | 0.3750 |
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- | 3.444 | 3.9823 | 37000 | 3.4486 | 0.3755 |
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- | 3.3707 | 4.0900 | 38000 | 3.4500 | 0.3761 |
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- | 3.3754 | 4.1976 | 39000 | 3.4473 | 0.3763 |
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- | 3.392 | 4.3052 | 40000 | 3.4433 | 0.3767 |
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- | 3.3969 | 4.4129 | 41000 | 3.4374 | 0.3773 |
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- | 3.4062 | 4.5205 | 42000 | 3.4324 | 0.3782 |
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- | 3.3706 | 4.6281 | 43000 | 3.4268 | 0.3784 |
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- | 3.407 | 4.7358 | 44000 | 3.4216 | 0.3794 |
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- | 3.385 | 4.8434 | 45000 | 3.4172 | 0.3795 |
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- | 3.3928 | 4.9510 | 46000 | 3.4112 | 0.3800 |
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- | 3.3105 | 5.0587 | 47000 | 3.4158 | 0.3801 |
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- | 3.3207 | 5.1663 | 48000 | 3.4145 | 0.3803 |
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- | 3.3359 | 5.2739 | 49000 | 3.4108 | 0.3807 |
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- | 3.3431 | 5.3816 | 50000 | 3.4053 | 0.3813 |
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- | 3.3256 | 5.4892 | 51000 | 3.3999 | 0.3821 |
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- | 3.3417 | 5.5968 | 52000 | 3.3972 | 0.3822 |
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- | 3.3248 | 5.7044 | 53000 | 3.3938 | 0.3826 |
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- | 3.3469 | 5.8121 | 54000 | 3.3861 | 0.3833 |
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- | 3.3445 | 5.9197 | 55000 | 3.3848 | 0.3832 |
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- | 3.2471 | 6.0273 | 56000 | 3.3878 | 0.3839 |
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- | 3.2697 | 6.1350 | 57000 | 3.3861 | 0.3839 |
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- | 3.2705 | 6.2426 | 58000 | 3.3844 | 0.3839 |
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- | 3.2824 | 6.3502 | 59000 | 3.3815 | 0.3846 |
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- | 3.2848 | 6.4579 | 60000 | 3.3737 | 0.3853 |
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- | 3.2926 | 6.5655 | 61000 | 3.3743 | 0.3853 |
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- | 3.3001 | 6.6731 | 62000 | 3.3672 | 0.3859 |
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- | 3.285 | 6.7808 | 63000 | 3.3637 | 0.3862 |
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- | 3.2812 | 6.8884 | 64000 | 3.3598 | 0.3865 |
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- | 3.2788 | 6.9960 | 65000 | 3.3560 | 0.3871 |
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- | 3.2324 | 7.1036 | 66000 | 3.3601 | 0.3871 |
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- | 3.2299 | 7.2113 | 67000 | 3.3598 | 0.3872 |
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- | 3.2138 | 7.3189 | 68000 | 3.3565 | 0.3876 |
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- | 3.2307 | 7.4265 | 69000 | 3.3512 | 0.3881 |
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- | 3.2237 | 7.5342 | 70000 | 3.3474 | 0.3885 |
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- | 3.2459 | 7.6418 | 71000 | 3.3448 | 0.3886 |
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- | 3.2524 | 7.7494 | 72000 | 3.3401 | 0.3893 |
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- | 3.2448 | 7.8571 | 73000 | 3.3385 | 0.3891 |
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- | 3.2453 | 7.9647 | 74000 | 3.3345 | 0.3898 |
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- | 3.1701 | 8.0723 | 75000 | 3.3382 | 0.3898 |
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- | 3.1943 | 8.1800 | 76000 | 3.3384 | 0.3899 |
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- | 3.1906 | 8.2876 | 77000 | 3.3345 | 0.3902 |
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- | 3.1759 | 8.3952 | 78000 | 3.3313 | 0.3906 |
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- | 3.1915 | 8.5029 | 79000 | 3.3280 | 0.3910 |
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- | 3.1977 | 8.6105 | 80000 | 3.3242 | 0.3915 |
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- | 3.1806 | 8.7181 | 81000 | 3.3226 | 0.3917 |
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- | 3.2022 | 8.8257 | 82000 | 3.3190 | 0.3920 |
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- | 3.1851 | 8.9334 | 83000 | 3.3163 | 0.3924 |
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- | 3.1297 | 9.0410 | 84000 | 3.3181 | 0.3923 |
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- | 3.1309 | 9.1486 | 85000 | 3.3175 | 0.3925 |
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- | 3.1235 | 9.2563 | 86000 | 3.3155 | 0.3928 |
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- | 3.1488 | 9.3639 | 87000 | 3.3130 | 0.3930 |
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- | 3.1455 | 9.4715 | 88000 | 3.3105 | 0.3933 |
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- | 3.1375 | 9.5792 | 89000 | 3.3093 | 0.3935 |
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- | 3.1281 | 9.6868 | 90000 | 3.3066 | 0.3939 |
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- | 3.14 | 9.7944 | 91000 | 3.3052 | 0.3940 |
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- | 3.1462 | 9.9021 | 92000 | 3.3026 | 0.3943 |
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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: 3.3010
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+ - Accuracy: 0.3945
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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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+ | 5.0974 | 0.1078 | 1000 | 5.0247 | 0.2269 |
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+ | 4.5993 | 0.2156 | 2000 | 4.5195 | 0.2694 |
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+ | 4.3178 | 0.3235 | 3000 | 4.2556 | 0.2971 |
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+ | 4.1673 | 0.4313 | 4000 | 4.0961 | 0.3120 |
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+ | 4.0543 | 0.5391 | 5000 | 3.9989 | 0.3202 |
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+ | 4.0007 | 0.6469 | 6000 | 3.9245 | 0.3274 |
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+ | 3.928 | 0.7547 | 7000 | 3.8680 | 0.3327 |
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+ | 3.8579 | 0.8625 | 8000 | 3.8217 | 0.3374 |
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+ | 3.8598 | 0.9704 | 9000 | 3.7847 | 0.3408 |
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+ | 3.7665 | 1.0782 | 10000 | 3.7521 | 0.3442 |
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+ | 3.7743 | 1.1860 | 11000 | 3.7252 | 0.3471 |
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+ | 3.7342 | 1.2938 | 12000 | 3.7023 | 0.3490 |
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+ | 3.7121 | 1.4016 | 13000 | 3.6798 | 0.3515 |
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+ | 3.7085 | 1.5094 | 14000 | 3.6600 | 0.3534 |
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+ | 3.669 | 1.6173 | 15000 | 3.6407 | 0.3553 |
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+ | 3.6691 | 1.7251 | 16000 | 3.6242 | 0.3572 |
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+ | 3.6442 | 1.8329 | 17000 | 3.6063 | 0.3587 |
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+ | 3.636 | 1.9407 | 18000 | 3.5935 | 0.3597 |
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+ | 3.5737 | 2.0485 | 19000 | 3.5847 | 0.3613 |
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+ | 3.579 | 2.1563 | 20000 | 3.5757 | 0.3622 |
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+ | 3.5659 | 2.2642 | 21000 | 3.5614 | 0.3637 |
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+ | 3.5765 | 2.3720 | 22000 | 3.5538 | 0.3644 |
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+ | 3.5435 | 2.4798 | 23000 | 3.5435 | 0.3657 |
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+ | 3.5367 | 2.5876 | 24000 | 3.5345 | 0.3667 |
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+ | 3.5316 | 2.6954 | 25000 | 3.5250 | 0.3671 |
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+ | 3.5378 | 2.8032 | 26000 | 3.5146 | 0.3684 |
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+ | 3.5476 | 2.9111 | 27000 | 3.5070 | 0.3694 |
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+ | 3.4485 | 3.0189 | 28000 | 3.5057 | 0.3699 |
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+ | 3.4338 | 3.1267 | 29000 | 3.5003 | 0.3707 |
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+ | 3.4561 | 3.2345 | 30000 | 3.4927 | 0.3712 |
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+ | 3.4624 | 3.3423 | 31000 | 3.4868 | 0.3718 |
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+ | 3.4618 | 3.4501 | 32000 | 3.4790 | 0.3729 |
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+ | 3.4664 | 3.5580 | 33000 | 3.4729 | 0.3733 |
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+ | 3.4623 | 3.6658 | 34000 | 3.4674 | 0.3736 |
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+ | 3.4655 | 3.7736 | 35000 | 3.4621 | 0.3749 |
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+ | 3.4556 | 3.8814 | 36000 | 3.4533 | 0.3750 |
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+ | 3.4524 | 3.9892 | 37000 | 3.4478 | 0.3758 |
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+ | 3.3686 | 4.0970 | 38000 | 3.4527 | 0.3760 |
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+ | 3.3679 | 4.2049 | 39000 | 3.4481 | 0.3770 |
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+ | 3.3931 | 4.3127 | 40000 | 3.4437 | 0.3770 |
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+ | 3.4004 | 4.4205 | 41000 | 3.4358 | 0.3778 |
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+ | 3.3908 | 4.5283 | 42000 | 3.4317 | 0.3783 |
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+ | 3.4003 | 4.6361 | 43000 | 3.4269 | 0.3785 |
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+ | 3.3915 | 4.7439 | 44000 | 3.4216 | 0.3793 |
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+ | 3.4107 | 4.8518 | 45000 | 3.4172 | 0.3795 |
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+ | 3.3766 | 4.9596 | 46000 | 3.4112 | 0.3802 |
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+ | 3.3192 | 5.0674 | 47000 | 3.4131 | 0.3807 |
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+ | 3.3176 | 5.1752 | 48000 | 3.4122 | 0.3811 |
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+ | 3.3479 | 5.2830 | 49000 | 3.4084 | 0.3813 |
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+ | 3.3449 | 5.3908 | 50000 | 3.4038 | 0.3817 |
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+ | 3.3478 | 5.4987 | 51000 | 3.4009 | 0.3818 |
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+ | 3.322 | 5.6065 | 52000 | 3.3949 | 0.3823 |
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+ | 3.3379 | 5.7143 | 53000 | 3.3901 | 0.3829 |
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+ | 3.3347 | 5.8221 | 54000 | 3.3852 | 0.3833 |
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+ | 3.3393 | 5.9299 | 55000 | 3.3831 | 0.3837 |
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+ | 3.2397 | 6.0377 | 56000 | 3.3860 | 0.3837 |
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+ | 3.2592 | 6.1456 | 57000 | 3.3850 | 0.3840 |
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+ | 3.2795 | 6.2534 | 58000 | 3.3818 | 0.3844 |
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+ | 3.2914 | 6.3612 | 59000 | 3.3779 | 0.3846 |
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+ | 3.2931 | 6.4690 | 60000 | 3.3754 | 0.3853 |
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+ | 3.2857 | 6.5768 | 61000 | 3.3688 | 0.3858 |
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+ | 3.3039 | 6.6846 | 62000 | 3.3650 | 0.3861 |
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+ | 3.2819 | 6.7925 | 63000 | 3.3613 | 0.3864 |
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+ | 3.2928 | 6.9003 | 64000 | 3.3568 | 0.3870 |
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+ | 3.1888 | 7.0081 | 65000 | 3.3578 | 0.3871 |
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+ | 3.2298 | 7.1159 | 66000 | 3.3615 | 0.3872 |
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+ | 3.2352 | 7.2237 | 67000 | 3.3592 | 0.3876 |
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+ | 3.233 | 7.3315 | 68000 | 3.3563 | 0.3879 |
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+ | 3.2228 | 7.4394 | 69000 | 3.3514 | 0.3881 |
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+ | 3.2302 | 7.5472 | 70000 | 3.3481 | 0.3885 |
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+ | 3.2571 | 7.6550 | 71000 | 3.3431 | 0.3890 |
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+ | 3.2565 | 7.7628 | 72000 | 3.3410 | 0.3894 |
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+ | 3.237 | 7.8706 | 73000 | 3.3360 | 0.3896 |
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+ | 3.2588 | 7.9784 | 74000 | 3.3328 | 0.3902 |
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+ | 3.1631 | 8.0863 | 75000 | 3.3371 | 0.3902 |
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+ | 3.1623 | 8.1941 | 76000 | 3.3360 | 0.3902 |
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+ | 3.1808 | 8.3019 | 77000 | 3.3335 | 0.3904 |
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+ | 3.1726 | 8.4097 | 78000 | 3.3312 | 0.3908 |
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+ | 3.1871 | 8.5175 | 79000 | 3.3258 | 0.3912 |
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+ | 3.2015 | 8.6253 | 80000 | 3.3230 | 0.3916 |
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+ | 3.1952 | 8.7332 | 81000 | 3.3201 | 0.3920 |
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+ | 3.1898 | 8.8410 | 82000 | 3.3171 | 0.3920 |
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+ | 3.1716 | 8.9488 | 83000 | 3.3131 | 0.3926 |
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+ | 3.133 | 9.0566 | 84000 | 3.3167 | 0.3926 |
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+ | 3.125 | 9.1644 | 85000 | 3.3157 | 0.3926 |
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+ | 3.1507 | 9.2722 | 86000 | 3.3139 | 0.3932 |
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+ | 3.1293 | 9.3801 | 87000 | 3.3116 | 0.3933 |
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+ | 3.1376 | 9.4879 | 88000 | 3.3085 | 0.3936 |
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+ | 3.1178 | 9.5957 | 89000 | 3.3066 | 0.3939 |
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+ | 3.1439 | 9.7035 | 90000 | 3.3038 | 0.3941 |
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+ | 3.1335 | 9.8113 | 91000 | 3.3029 | 0.3943 |
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+ | 3.1264 | 9.9191 | 92000 | 3.3010 | 0.3945 |
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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:b02f032c215bd64dd110f2e8c433441b33f31bc0d93bcfb960c02bf9bf65ad43
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  size 503128704
 
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  version https://git-lfs.github.com/spec/v1
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+ oid sha256:899f5fb2d12c887980cf1fe7e16419632868e2d76d705615dc3e7f4262114b6d
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  size 503128704