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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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xet
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End of training

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  1. README.md +40 -24
  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: 0.6154
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- - Accuracy: 0.7362
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- - Auc Score: 0.8016
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- - F1: 0.7714
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- - Precision: 0.7557
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- - Recall: 0.7878
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  ## Model description
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@@ -44,8 +44,8 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 3e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
@@ -55,22 +55,38 @@ 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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- | 0.6869 | 0.1845 | 100 | 0.6557 | 0.6338 | 0.6812 | 0.7327 | 0.6235 | 0.8882 |
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- | 0.655 | 0.3690 | 200 | 0.6146 | 0.6527 | 0.7396 | 0.6440 | 0.7652 | 0.5559 |
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- | 0.6269 | 0.5535 | 300 | 0.5991 | 0.6850 | 0.7517 | 0.7065 | 0.7459 | 0.6710 |
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- | 0.6089 | 0.7380 | 400 | 0.6444 | 0.6485 | 0.7632 | 0.6182 | 0.8003 | 0.5037 |
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- | 0.5962 | 0.9225 | 500 | 0.6072 | 0.6827 | 0.7764 | 0.7673 | 0.6551 | 0.9257 |
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- | 0.5633 | 1.1070 | 600 | 0.5957 | 0.6960 | 0.7767 | 0.7685 | 0.6745 | 0.8931 |
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- | 0.5067 | 1.2915 | 700 | 0.6133 | 0.7196 | 0.7900 | 0.7778 | 0.7042 | 0.8686 |
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- | 0.505 | 1.4760 | 800 | 0.5766 | 0.7076 | 0.7703 | 0.7414 | 0.7408 | 0.7420 |
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- | 0.5115 | 1.6605 | 900 | 0.5415 | 0.7348 | 0.8011 | 0.7823 | 0.7295 | 0.8433 |
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- | 0.5027 | 1.8450 | 1000 | 0.5837 | 0.7163 | 0.7949 | 0.7755 | 0.7015 | 0.8669 |
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- | 0.4695 | 2.0295 | 1100 | 0.5699 | 0.7173 | 0.7889 | 0.7686 | 0.7149 | 0.8310 |
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- | 0.4032 | 2.2140 | 1200 | 0.6357 | 0.7145 | 0.7865 | 0.7718 | 0.7036 | 0.8547 |
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- | 0.3833 | 2.3985 | 1300 | 0.6236 | 0.7292 | 0.8014 | 0.7697 | 0.7409 | 0.8008 |
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- | 0.3924 | 2.5830 | 1400 | 0.6533 | 0.7103 | 0.7970 | 0.7784 | 0.6855 | 0.9004 |
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- | 0.3673 | 2.7675 | 1500 | 0.6303 | 0.7260 | 0.8004 | 0.7729 | 0.7268 | 0.8253 |
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- | 0.3749 | 2.9520 | 1600 | 0.6154 | 0.7362 | 0.8016 | 0.7714 | 0.7557 | 0.7878 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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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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  The following hyperparameters were used during training:
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  - learning_rate: 3e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
 
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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
model.safetensors CHANGED
@@ -1,3 +1,3 @@
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