|
|
--- |
|
|
library_name: transformers |
|
|
license: mit |
|
|
base_model: FacebookAI/roberta-base |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
- precision |
|
|
- recall |
|
|
- f1 |
|
|
model-index: |
|
|
- name: roberta-hate-speech-detection |
|
|
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. --> |
|
|
|
|
|
# roberta-hate-speech-detection |
|
|
|
|
|
This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.4354 |
|
|
- Accuracy: 0.808 |
|
|
- Auc: 0.898 |
|
|
- Precision: 0.8081 |
|
|
- Recall: 0.8077 |
|
|
- F1: 0.8078 |
|
|
|
|
|
## 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: 1e-05 |
|
|
- train_batch_size: 64 |
|
|
- eval_batch_size: 64 |
|
|
- 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 |
|
|
- lr_scheduler_warmup_steps: 500 |
|
|
- num_epochs: 20 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc | Precision | Recall | F1 | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:---------:|:------:|:------:| |
|
|
| 0.691 | 1.0 | 188 | 0.6680 | 0.626 | 0.662 | 0.6289 | 0.6265 | 0.6222 | |
|
|
| 0.6036 | 2.0 | 376 | 0.5378 | 0.726 | 0.807 | 0.7273 | 0.7257 | 0.7245 | |
|
|
| 0.5107 | 3.0 | 564 | 0.5570 | 0.742 | 0.85 | 0.7668 | 0.7417 | 0.7371 | |
|
|
| 0.4531 | 4.0 | 752 | 0.4833 | 0.778 | 0.88 | 0.7862 | 0.7783 | 0.7759 | |
|
|
| 0.4077 | 5.0 | 940 | 0.4477 | 0.81 | 0.89 | 0.8131 | 0.8103 | 0.8101 | |
|
|
| 0.3567 | 6.0 | 1128 | 0.4229 | 0.832 | 0.902 | 0.8316 | 0.8316 | 0.8316 | |
|
|
| 0.3202 | 7.0 | 1316 | 0.4174 | 0.827 | 0.907 | 0.8273 | 0.8269 | 0.8269 | |
|
|
| 0.299 | 8.0 | 1504 | 0.4531 | 0.822 | 0.909 | 0.8262 | 0.8222 | 0.8220 | |
|
|
| 0.2625 | 9.0 | 1692 | 0.4289 | 0.839 | 0.912 | 0.8390 | 0.8389 | 0.8389 | |
|
|
| 0.2457 | 10.0 | 1880 | 0.4246 | 0.846 | 0.915 | 0.8457 | 0.8455 | 0.8456 | |
|
|
| 0.2173 | 11.0 | 2068 | 0.4783 | 0.844 | 0.914 | 0.8435 | 0.8435 | 0.8435 | |
|
|
| 0.1956 | 12.0 | 2256 | 0.4893 | 0.845 | 0.915 | 0.8479 | 0.8449 | 0.8448 | |
|
|
| 0.1761 | 13.0 | 2444 | 0.5208 | 0.837 | 0.914 | 0.8420 | 0.8369 | 0.8366 | |
|
|
| 0.1627 | 14.0 | 2632 | 0.5077 | 0.842 | 0.918 | 0.8427 | 0.8415 | 0.8416 | |
|
|
| 0.1482 | 15.0 | 2820 | 0.5581 | 0.835 | 0.917 | 0.8408 | 0.8349 | 0.8345 | |
|
|
| 0.1437 | 16.0 | 3008 | 0.5135 | 0.854 | 0.921 | 0.8545 | 0.8542 | 0.8542 | |
|
|
| 0.1315 | 17.0 | 3196 | 0.5428 | 0.846 | 0.921 | 0.8492 | 0.8462 | 0.8461 | |
|
|
| 0.1209 | 18.0 | 3384 | 0.5382 | 0.853 | 0.921 | 0.8530 | 0.8529 | 0.8529 | |
|
|
| 0.1186 | 19.0 | 3572 | 0.5839 | 0.844 | 0.92 | 0.8459 | 0.8435 | 0.8435 | |
|
|
| 0.105 | 20.0 | 3760 | 0.5757 | 0.845 | 0.921 | 0.8468 | 0.8449 | 0.8448 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.52.3 |
|
|
- Pytorch 2.6.0+cu124 |
|
|
- Datasets 3.6.0 |
|
|
- Tokenizers 0.21.1 |
|
|
|
