| --- |
| library_name: transformers |
| base_model: cardiffnlp/twitter-roberta-base-hate |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| - precision |
| - recall |
| model-index: |
| - name: test_dir_model3 |
| 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. --> |
|
|
| # test_dir_model3 |
|
|
| This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-hate](https://huggingface.co/cardiffnlp/twitter-roberta-base-hate) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.2679 |
| - Accuracy: 0.8783 |
| - F1: 0.6997 |
| - Precision: 0.8118 |
| - Recall: 0.6915 |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - num_epochs: 10 |
| - label_smoothing_factor: 0.1 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | No log | 1.0 | 35 | 1.1935 | 0.7304 | 0.3920 | 0.3732 | 0.4740 | |
| | No log | 2.0 | 70 | 1.2142 | 0.8348 | 0.6136 | 0.6065 | 0.6625 | |
| | 0.9237 | 3.0 | 105 | 1.3719 | 0.8783 | 0.7167 | 0.7802 | 0.7244 | |
| | 0.9237 | 4.0 | 140 | 1.5517 | 0.8696 | 0.7135 | 0.7685 | 0.7367 | |
| | 0.9237 | 5.0 | 175 | 1.9028 | 0.8870 | 0.7282 | 0.7874 | 0.7423 | |
| | 0.3387 | 6.0 | 210 | 2.0006 | 0.8696 | 0.6333 | 0.775 | 0.6708 | |
| | 0.3387 | 7.0 | 245 | 2.1684 | 0.8783 | 0.6997 | 0.8118 | 0.6915 | |
| | 0.3387 | 8.0 | 280 | 2.1672 | 0.8696 | 0.6958 | 0.7972 | 0.7038 | |
| | 0.119 | 9.0 | 315 | 2.2526 | 0.8783 | 0.6997 | 0.8118 | 0.6915 | |
| | 0.119 | 10.0 | 350 | 2.2679 | 0.8783 | 0.6997 | 0.8118 | 0.6915 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.57.3 |
| - Pytorch 2.9.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.1 |
| |
