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franac1
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hate_speech

Text Classification
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Safetensors
electra
Generated from Trainer
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End of training

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  1. README.md +41 -41
  2. model.safetensors +1 -1
README.md CHANGED
@@ -19,12 +19,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model was trained from scratch on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7687
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- - Accuracy: 0.8017
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- - Auc Score: 0.8728
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- - F1: 0.8298
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- - Precision: 0.8074
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- - Recall: 0.8534
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  ## Model description
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@@ -55,43 +55,43 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc Score | F1 | Precision | Recall |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:---------:|:------:|
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- | 0.6445 | 0.0923 | 100 | 0.5441 | 0.7435 | 0.8052 | 0.7751 | 0.7701 | 0.7801 |
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- | 0.5767 | 0.1845 | 200 | 0.5260 | 0.7555 | 0.8345 | 0.7721 | 0.8179 | 0.7313 |
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- | 0.5126 | 0.2768 | 300 | 0.5090 | 0.7629 | 0.8450 | 0.8068 | 0.7493 | 0.8738 |
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- | 0.4723 | 0.3690 | 400 | 0.5557 | 0.7417 | 0.8505 | 0.7363 | 0.8728 | 0.6368 |
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- | 0.511 | 0.4613 | 500 | 0.4766 | 0.7823 | 0.8525 | 0.8106 | 0.7991 | 0.8225 |
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- | 0.5082 | 0.5535 | 600 | 0.4947 | 0.7915 | 0.8565 | 0.8239 | 0.7900 | 0.8607 |
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- | 0.4494 | 0.6458 | 700 | 0.4976 | 0.7763 | 0.8560 | 0.8032 | 0.8003 | 0.8062 |
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- | 0.4816 | 0.7380 | 800 | 0.4648 | 0.7827 | 0.8624 | 0.8111 | 0.7992 | 0.8233 |
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- | 0.4665 | 0.8303 | 900 | 0.4649 | 0.7887 | 0.8656 | 0.8200 | 0.7926 | 0.8493 |
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- | 0.5226 | 0.9225 | 1000 | 0.4537 | 0.7929 | 0.8666 | 0.8158 | 0.8222 | 0.8094 |
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- | 0.4643 | 1.0148 | 1100 | 0.4747 | 0.7998 | 0.8676 | 0.8287 | 0.8040 | 0.8550 |
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- | 0.3617 | 1.1070 | 1200 | 0.5402 | 0.7943 | 0.8668 | 0.8213 | 0.8084 | 0.8347 |
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- | 0.3439 | 1.1993 | 1300 | 0.5924 | 0.7966 | 0.8703 | 0.8267 | 0.7988 | 0.8567 |
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- | 0.3482 | 1.2915 | 1400 | 0.5369 | 0.8003 | 0.8681 | 0.8287 | 0.8060 | 0.8526 |
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- | 0.3855 | 1.3838 | 1500 | 0.5213 | 0.7966 | 0.8702 | 0.8205 | 0.8202 | 0.8208 |
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- | 0.335 | 1.4760 | 1600 | 0.5387 | 0.7929 | 0.8702 | 0.8176 | 0.8159 | 0.8192 |
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- | 0.382 | 1.5683 | 1700 | 0.5267 | 0.7924 | 0.8710 | 0.8109 | 0.8377 | 0.7858 |
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- | 0.341 | 1.6605 | 1800 | 0.6565 | 0.7957 | 0.8722 | 0.8293 | 0.7871 | 0.8762 |
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- | 0.3492 | 1.7528 | 1900 | 0.5635 | 0.7957 | 0.8725 | 0.8298 | 0.7855 | 0.8795 |
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- | 0.3861 | 1.8450 | 2000 | 0.5204 | 0.7998 | 0.8752 | 0.8281 | 0.8063 | 0.8510 |
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- | 0.3451 | 1.9373 | 2100 | 0.5854 | 0.7984 | 0.8757 | 0.8316 | 0.7893 | 0.8787 |
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- | 0.2915 | 2.0295 | 2200 | 0.6308 | 0.8021 | 0.8744 | 0.8354 | 0.7897 | 0.8868 |
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- | 0.2264 | 2.1218 | 2300 | 0.7711 | 0.7984 | 0.8741 | 0.8234 | 0.8172 | 0.8298 |
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- | 0.244 | 2.2140 | 2400 | 0.7302 | 0.8030 | 0.8742 | 0.8346 | 0.7960 | 0.8770 |
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- | 0.2477 | 2.3063 | 2500 | 0.8263 | 0.7915 | 0.8721 | 0.8154 | 0.8180 | 0.8127 |
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- | 0.2356 | 2.3985 | 2600 | 0.8275 | 0.7980 | 0.8734 | 0.8301 | 0.7926 | 0.8713 |
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- | 0.2122 | 2.4908 | 2700 | 0.8132 | 0.7980 | 0.8723 | 0.8234 | 0.8155 | 0.8314 |
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- | 0.2443 | 2.5830 | 2800 | 0.7874 | 0.8007 | 0.8728 | 0.8269 | 0.8139 | 0.8404 |
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- | 0.2275 | 2.6753 | 2900 | 0.7503 | 0.8003 | 0.8738 | 0.8322 | 0.7938 | 0.8746 |
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- | 0.2476 | 2.7675 | 3000 | 0.7822 | 0.7957 | 0.8731 | 0.8206 | 0.8163 | 0.8249 |
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- | 0.1961 | 2.8598 | 3100 | 0.7780 | 0.8021 | 0.8731 | 0.8304 | 0.8071 | 0.8550 |
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- | 0.2536 | 2.9520 | 3200 | 0.7687 | 0.8017 | 0.8728 | 0.8298 | 0.8074 | 0.8534 |
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  ### Framework versions
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- - Transformers 4.52.4
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- - Pytorch 2.6.0+cu124
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  - Datasets 3.6.0
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- - Tokenizers 0.21.1
 
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  This model was trained from scratch on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8688
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+ - Accuracy: 0.7970
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+ - Auc Score: 0.8778
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+ - F1: 0.8222
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+ - Precision: 0.7921
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+ - Recall: 0.8546
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc Score | F1 | Precision | Recall |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:---------:|:------:|
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+ | 0.6298 | 0.0923 | 100 | 0.5147 | 0.75 | 0.8339 | 0.7734 | 0.7696 | 0.7773 |
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+ | 0.5265 | 0.1845 | 200 | 0.5786 | 0.7279 | 0.8387 | 0.7065 | 0.8659 | 0.5966 |
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+ | 0.53 | 0.2768 | 300 | 0.4984 | 0.7721 | 0.8519 | 0.8072 | 0.7536 | 0.8689 |
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+ | 0.533 | 0.3690 | 400 | 0.4937 | 0.7620 | 0.8575 | 0.8008 | 0.7407 | 0.8714 |
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+ | 0.484 | 0.4613 | 500 | 0.5134 | 0.7597 | 0.8538 | 0.8045 | 0.7268 | 0.9008 |
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+ | 0.4723 | 0.5535 | 600 | 0.4743 | 0.7818 | 0.8623 | 0.8015 | 0.8005 | 0.8025 |
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+ | 0.4753 | 0.6458 | 700 | 0.6482 | 0.7274 | 0.8661 | 0.7921 | 0.6812 | 0.9462 |
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+ | 0.5042 | 0.7380 | 800 | 0.4545 | 0.7864 | 0.8671 | 0.8021 | 0.8164 | 0.7882 |
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+ | 0.5203 | 0.8303 | 900 | 0.4609 | 0.7837 | 0.8684 | 0.8119 | 0.7767 | 0.8504 |
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+ | 0.454 | 0.9225 | 1000 | 0.4819 | 0.7754 | 0.8671 | 0.7765 | 0.8554 | 0.7109 |
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+ | 0.4599 | 1.0148 | 1100 | 0.5349 | 0.7864 | 0.8717 | 0.8010 | 0.8197 | 0.7832 |
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+ | 0.3534 | 1.1070 | 1200 | 0.5687 | 0.7818 | 0.8706 | 0.8040 | 0.7931 | 0.8151 |
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+ | 0.328 | 1.1993 | 1300 | 0.6812 | 0.7809 | 0.8649 | 0.8093 | 0.7748 | 0.8471 |
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+ | 0.3662 | 1.2915 | 1400 | 0.5995 | 0.7837 | 0.8799 | 0.8172 | 0.7622 | 0.8807 |
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+ | 0.385 | 1.3838 | 1500 | 0.4919 | 0.7929 | 0.8747 | 0.8150 | 0.7995 | 0.8311 |
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+ | 0.3312 | 1.4760 | 1600 | 0.6258 | 0.7947 | 0.8778 | 0.8142 | 0.8091 | 0.8193 |
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+ | 0.3924 | 1.5683 | 1700 | 0.5400 | 0.7924 | 0.8731 | 0.8154 | 0.7965 | 0.8353 |
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+ | 0.3304 | 1.6605 | 1800 | 0.6309 | 0.7929 | 0.8831 | 0.8178 | 0.7906 | 0.8471 |
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+ | 0.3599 | 1.7528 | 1900 | 0.6720 | 0.7966 | 0.8793 | 0.8165 | 0.8087 | 0.8244 |
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+ | 0.4077 | 1.8450 | 2000 | 0.6728 | 0.7883 | 0.8833 | 0.8217 | 0.7639 | 0.8891 |
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+ | 0.3038 | 1.9373 | 2100 | 0.6785 | 0.7938 | 0.8854 | 0.8216 | 0.7825 | 0.8647 |
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+ | 0.2641 | 2.0295 | 2200 | 0.7032 | 0.7984 | 0.8821 | 0.816 | 0.8177 | 0.8143 |
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+ | 0.2258 | 2.1218 | 2300 | 0.8256 | 0.7860 | 0.8774 | 0.8180 | 0.7669 | 0.8765 |
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+ | 0.2048 | 2.2140 | 2400 | 0.8105 | 0.8026 | 0.8747 | 0.8197 | 0.8218 | 0.8176 |
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+ | 0.23 | 2.3063 | 2500 | 0.9278 | 0.7892 | 0.8731 | 0.8211 | 0.7685 | 0.8815 |
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+ | 0.2274 | 2.3985 | 2600 | 0.8879 | 0.7911 | 0.8733 | 0.8011 | 0.8390 | 0.7664 |
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+ | 0.1667 | 2.4908 | 2700 | 0.9328 | 0.7915 | 0.8784 | 0.8192 | 0.7817 | 0.8605 |
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+ | 0.2208 | 2.5830 | 2800 | 0.8900 | 0.7989 | 0.8797 | 0.8185 | 0.8111 | 0.8261 |
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+ | 0.2478 | 2.6753 | 2900 | 0.9207 | 0.7947 | 0.8799 | 0.8229 | 0.7816 | 0.8689 |
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+ | 0.26 | 2.7675 | 3000 | 0.8699 | 0.7943 | 0.8759 | 0.8202 | 0.7884 | 0.8546 |
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+ | 0.2079 | 2.8598 | 3100 | 0.8664 | 0.7952 | 0.8768 | 0.8202 | 0.7914 | 0.8513 |
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+ | 0.1781 | 2.9520 | 3200 | 0.8688 | 0.7970 | 0.8778 | 0.8222 | 0.7921 | 0.8546 |
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  ### Framework versions
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+ - Transformers 4.53.0
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+ - Pytorch 2.7.1+cu126
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  - Datasets 3.6.0
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+ - Tokenizers 0.21.2
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