--- library_name: transformers tags: - generated_from_trainer metrics: - accuracy model-index: - name: 100M__495 results: [] --- # 100M__495 This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 3.4676 - Accuracy: 0.3760 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0006 - train_batch_size: 32 - eval_batch_size: 16 - seed: 495 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.98) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 100 - num_epochs: 50 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Accuracy | Validation Loss | |:-------------:|:-------:|:-----:|:--------:|:---------------:| | 5.1665 | 0.1078 | 1000 | 0.2206 | 5.0912 | | 4.6555 | 0.2156 | 2000 | 0.2607 | 4.6008 | | 4.3901 | 0.3235 | 3000 | 0.2916 | 4.2963 | | 4.2075 | 0.4313 | 4000 | 0.3082 | 4.1342 | | 4.0819 | 0.5391 | 5000 | 0.3186 | 4.0228 | | 4.0201 | 0.6469 | 6000 | 0.3257 | 3.9409 | | 3.9519 | 0.7547 | 7000 | 0.3312 | 3.8853 | | 3.8917 | 0.8625 | 8000 | 0.3359 | 3.8361 | | 3.8592 | 0.9704 | 9000 | 0.3404 | 3.7949 | | 3.7811 | 1.0782 | 10000 | 0.3437 | 3.7621 | | 3.7908 | 1.1860 | 11000 | 0.3460 | 3.7343 | | 3.7514 | 1.2938 | 12000 | 0.3482 | 3.7092 | | 3.7207 | 1.4016 | 13000 | 0.3513 | 3.6841 | | 3.7092 | 1.5094 | 14000 | 0.3533 | 3.6657 | | 3.6968 | 1.6173 | 15000 | 0.3550 | 3.6474 | | 3.6724 | 1.7251 | 16000 | 0.3571 | 3.6263 | | 3.6737 | 1.8329 | 17000 | 0.3582 | 3.6162 | | 3.6477 | 1.9407 | 18000 | 0.3598 | 3.5972 | | 3.5922 | 2.0485 | 19000 | 0.3611 | 3.5889 | | 3.5706 | 2.1563 | 20000 | 0.3621 | 3.5809 | | 3.5568 | 2.2642 | 21000 | 0.3631 | 3.5704 | | 3.5596 | 2.3720 | 22000 | 0.3645 | 3.5584 | | 3.5529 | 2.4798 | 23000 | 0.3655 | 3.5451 | | 3.5466 | 2.5876 | 24000 | 0.3665 | 3.5379 | | 3.555 | 2.6954 | 25000 | 0.3674 | 3.5254 | | 3.5597 | 2.8032 | 26000 | 0.3684 | 3.5180 | | 3.5422 | 2.9111 | 27000 | 0.3693 | 3.5087 | | 3.4422 | 3.0189 | 28000 | 0.3700 | 3.5041 | | 3.4594 | 3.1267 | 29000 | 0.3709 | 3.4994 | | 3.4767 | 3.2345 | 30000 | 0.3715 | 3.4932 | | 3.4629 | 3.3423 | 31000 | 0.3725 | 3.4884 | | 3.471 | 3.4501 | 32000 | 0.3728 | 3.4814 | | 3.4594 | 3.5580 | 33000 | 0.3735 | 3.4750 | | 3.4814 | 3.6658 | 34000 | 0.3739 | 3.4692 | | 3.4593 | 3.7736 | 35000 | 0.3747 | 3.4629 | | 3.4435 | 3.8814 | 36000 | 0.3756 | 3.4561 | | 3.4633 | 3.9892 | 37000 | 0.3759 | 3.4494 | | 3.381 | 4.0970 | 38000 | 0.3766 | 3.4523 | | 3.3899 | 4.2049 | 39000 | 0.3769 | 3.4458 | | 3.3917 | 4.3127 | 40000 | 0.3774 | 3.4431 | | 3.4098 | 4.4205 | 41000 | 0.3781 | 3.4349 | | 3.4073 | 4.5283 | 42000 | 0.3784 | 3.4332 | | 3.3993 | 4.6361 | 43000 | 0.3786 | 3.4270 | | 3.4026 | 4.7439 | 44000 | 0.3797 | 3.4206 | | 3.407 | 4.8518 | 45000 | 0.3798 | 3.4162 | | 3.3882 | 4.9596 | 46000 | 0.3807 | 3.4124 | | 3.3153 | 5.0674 | 47000 | 0.3809 | 3.4160 | | 3.3206 | 5.1752 | 48000 | 0.3811 | 3.4111 | | 3.3424 | 5.2830 | 49000 | 0.3814 | 3.4074 | | 3.3458 | 5.3908 | 50000 | 0.3819 | 3.4056 | | 3.3476 | 5.4987 | 51000 | 0.3825 | 3.4017 | | 3.3541 | 5.6065 | 52000 | 0.3827 | 3.3958 | | 3.347 | 5.7143 | 53000 | 0.3831 | 3.3918 | | 3.3347 | 5.8221 | 54000 | 0.3836 | 3.3862 | | 3.3565 | 5.9299 | 55000 | 0.3844 | 3.3812 | | 3.2551 | 6.0377 | 56000 | 0.3845 | 3.3851 | | 3.2716 | 6.1456 | 57000 | 0.3843 | 3.3840 | | 3.2895 | 6.2534 | 58000 | 0.3848 | 3.3813 | | 3.2759 | 6.3612 | 59000 | 0.3856 | 3.3767 | | 3.2909 | 6.4690 | 60000 | 0.3853 | 3.3733 | | 3.2835 | 6.5768 | 61000 | 0.3859 | 3.3691 | | 3.3046 | 6.6846 | 62000 | 0.3865 | 3.3650 | | 3.2794 | 6.7925 | 63000 | 0.3867 | 3.3618 | | 3.2831 | 6.9003 | 64000 | 0.3873 | 3.3556 | | 3.2134 | 7.0081 | 65000 | 0.3874 | 3.3601 | | 3.2066 | 7.1159 | 66000 | 0.3873 | 3.3606 | | 3.2313 | 7.2237 | 67000 | 0.3881 | 3.3570 | | 3.2319 | 7.3315 | 68000 | 0.3881 | 3.3540 | | 3.2282 | 7.4394 | 69000 | 0.3882 | 3.3505 | | 3.2386 | 7.5472 | 70000 | 0.3889 | 3.3455 | | 3.233 | 7.6550 | 71000 | 0.3891 | 3.3429 | | 3.2386 | 7.7628 | 72000 | 0.3898 | 3.3377 | | 3.247 | 7.8706 | 73000 | 0.3899 | 3.3356 | | 3.2571 | 7.9784 | 74000 | 0.3908 | 3.3312 | | 3.1695 | 8.0863 | 75000 | 0.3905 | 3.3377 | | 3.1903 | 8.1941 | 76000 | 0.3906 | 3.3351 | | 3.1892 | 8.3019 | 77000 | 0.3909 | 3.3317 | | 3.1795 | 8.4097 | 78000 | 0.3912 | 3.3293 | | 3.179 | 8.5175 | 79000 | 0.3916 | 3.3260 | | 3.2147 | 8.6253 | 80000 | 0.3919 | 3.3226 | | 3.1679 | 8.7332 | 81000 | 0.3922 | 3.3194 | | 3.1853 | 8.8410 | 82000 | 0.3925 | 3.3157 | | 3.1983 | 8.9488 | 83000 | 0.3929 | 3.3126 | | 3.1342 | 9.0566 | 84000 | 0.3928 | 3.3160 | | 3.1281 | 9.1644 | 85000 | 0.3930 | 3.3144 | | 3.129 | 9.2722 | 86000 | 0.3934 | 3.3116 | | 3.1315 | 9.3801 | 87000 | 0.3937 | 3.3096 | | 3.1295 | 9.4879 | 88000 | 0.3940 | 3.3074 | | 3.1314 | 9.5957 | 89000 | 0.3942 | 3.3044 | | 3.1393 | 9.7035 | 90000 | 0.3945 | 3.3022 | | 3.1482 | 9.8113 | 91000 | 0.3948 | 3.3000 | | 3.1491 | 9.9191 | 92000 | 0.3950 | 3.2984 | | 3.3064 | 10.0270 | 93000 | 3.4581 | 0.3773 | | 3.3807 | 10.1348 | 94000 | 3.4690 | 0.3764 | | 3.3886 | 10.2426 | 95000 | 3.4676 | 0.3760 | ### Framework versions - Transformers 4.47.0.dev0 - Pytorch 2.5.0+cu124 - Datasets 3.0.2 - Tokenizers 0.20.1