metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: BERT-cyberbullying-classifier-DirectFeatures
results: []
BERT-cyberbullying-classifier-DirectFeatures
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2471
- Accuracy: 0.9010
- F1: 0.8939
- Precision: 0.8993
- Recall: 0.9010
- Auc: 0.9337
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: 16
- eval_batch_size: 16
- seed: 22002423
- 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: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Auc |
|---|---|---|---|---|---|---|---|---|
| 0.2739 | 1.0 | 541 | 0.2423 | 0.9047 | 0.8938 | 0.9129 | 0.9047 | 0.9284 |
| 0.2137 | 2.0 | 1082 | 0.2471 | 0.9010 | 0.8939 | 0.8993 | 0.9010 | 0.9337 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1