| | --- |
| | library_name: transformers |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | - precision |
| | - recall |
| | model-index: |
| | - name: hate_speech |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # hate_speech |
| | |
| | This model was trained from scratch on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.7742 |
| | - Model Preparation Time: 0.0024 |
| | - Accuracy: 0.8037 |
| | - Auc Score: 0.8861 |
| | - F1: 0.8318 |
| | - Precision: 0.8010 |
| | - Recall: 0.8651 |
| | |
| | ## 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: 3e-05 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - num_epochs: 3 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy | Auc Score | F1 | Precision | Recall | |
| | |:-------------:|:------:|:----:|:---------------:|:----------------------:|:--------:|:---------:|:------:|:---------:|:------:| |
| | | 0.6024 | 0.1054 | 100 | 0.6052 | 0.0024 | 0.6806 | 0.7925 | 0.6496 | 0.8453 | 0.5274 | |
| | | 0.5439 | 0.2107 | 200 | 0.5120 | 0.0024 | 0.7514 | 0.8372 | 0.7941 | 0.7419 | 0.8542 | |
| | | 0.515 | 0.3161 | 300 | 0.5180 | 0.0024 | 0.7538 | 0.8469 | 0.8035 | 0.7278 | 0.8969 | |
| | | 0.5225 | 0.4215 | 400 | 0.5000 | 0.0024 | 0.7698 | 0.8393 | 0.7863 | 0.8210 | 0.7544 | |
| | | 0.4935 | 0.5269 | 500 | 0.5008 | 0.0024 | 0.768 | 0.8457 | 0.7961 | 0.7855 | 0.8070 | |
| | | 0.5196 | 0.6322 | 600 | 0.5069 | 0.0024 | 0.7674 | 0.8473 | 0.8023 | 0.767 | 0.8410 | |
| | | 0.4918 | 0.7376 | 700 | 0.5011 | 0.0024 | 0.7655 | 0.8565 | 0.8109 | 0.7407 | 0.8958 | |
| | | 0.5182 | 0.8430 | 800 | 0.4873 | 0.0024 | 0.7902 | 0.8616 | 0.8150 | 0.8067 | 0.8235 | |
| | | 0.4749 | 0.9484 | 900 | 0.4606 | 0.0024 | 0.7815 | 0.8674 | 0.8109 | 0.7886 | 0.8344 | |
| | | 0.4042 | 1.0537 | 1000 | 0.5453 | 0.0024 | 0.7852 | 0.8735 | 0.8211 | 0.7709 | 0.8783 | |
| | | 0.3593 | 1.1591 | 1100 | 0.5650 | 0.0024 | 0.7791 | 0.8745 | 0.8193 | 0.7572 | 0.8925 | |
| | | 0.3911 | 1.2645 | 1200 | 0.5108 | 0.0024 | 0.8025 | 0.8783 | 0.8264 | 0.8154 | 0.8377 | |
| | | 0.3445 | 1.3699 | 1300 | 0.6231 | 0.0024 | 0.7902 | 0.8815 | 0.8265 | 0.7711 | 0.8904 | |
| | | 0.4027 | 1.4752 | 1400 | 0.5336 | 0.0024 | 0.8062 | 0.8796 | 0.8239 | 0.8404 | 0.8081 | |
| | | 0.3058 | 1.5806 | 1500 | 0.6094 | 0.0024 | 0.7957 | 0.8760 | 0.8232 | 0.8002 | 0.8476 | |
| | | 0.3535 | 1.6860 | 1600 | 0.5834 | 0.0024 | 0.7951 | 0.8810 | 0.8254 | 0.7910 | 0.8629 | |
| | | 0.3713 | 1.7914 | 1700 | 0.5286 | 0.0024 | 0.7969 | 0.8817 | 0.8278 | 0.7898 | 0.8695 | |
| | | 0.359 | 1.8967 | 1800 | 0.5292 | 0.0024 | 0.8086 | 0.8819 | 0.8290 | 0.8313 | 0.8268 | |
| | | 0.3762 | 2.0021 | 1900 | 0.5222 | 0.0024 | 0.8037 | 0.8814 | 0.8297 | 0.8085 | 0.8520 | |
| | | 0.2101 | 2.1075 | 2000 | 0.6738 | 0.0024 | 0.8055 | 0.8793 | 0.8271 | 0.8253 | 0.8289 | |
| | | 0.2307 | 2.2129 | 2100 | 0.7485 | 0.0024 | 0.8012 | 0.8845 | 0.8324 | 0.7901 | 0.8794 | |
| | | 0.2403 | 2.3182 | 2200 | 0.7186 | 0.0024 | 0.8049 | 0.8818 | 0.8322 | 0.8045 | 0.8618 | |
| | | 0.221 | 2.4236 | 2300 | 0.7233 | 0.0024 | 0.8074 | 0.8818 | 0.8334 | 0.8097 | 0.8586 | |
| | | 0.2112 | 2.5290 | 2400 | 0.7259 | 0.0024 | 0.8123 | 0.8844 | 0.8345 | 0.8260 | 0.8432 | |
| | | 0.2155 | 2.6344 | 2500 | 0.7302 | 0.0024 | 0.8117 | 0.8854 | 0.8342 | 0.8244 | 0.8443 | |
| | | 0.1997 | 2.7397 | 2600 | 0.7658 | 0.0024 | 0.8074 | 0.8832 | 0.8289 | 0.8266 | 0.8311 | |
| | | 0.2761 | 2.8451 | 2700 | 0.7838 | 0.0024 | 0.8037 | 0.8869 | 0.8334 | 0.7956 | 0.875 | |
| | | 0.1878 | 2.9505 | 2800 | 0.7742 | 0.0024 | 0.8037 | 0.8861 | 0.8318 | 0.8010 | 0.8651 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.53.0 |
| | - Pytorch 2.7.1+cu126 |
| | - Datasets 3.6.0 |
| | - Tokenizers 0.21.2 |
| | |
