final_model_toxicity_classification

This model is a fine-tuned version of distilbert-base-uncased on the jigsaw_toxicity_pred dataset. It achieves the following results on the evaluation set:

• Loss: 0.2702
• F1: 0.6776
• Accuracy: 0.921

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: 4.910748967246961e-05
• train_batch_size: 32
• 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: 2
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy
0.0959	1.0	4987	0.1663	0.7248	0.94
0.0527	2.0	9974	0.2702	0.6776	0.921

Framework versions

• Transformers 4.52.4
• Pytorch 2.6.0+cu124
• Datasets 3.6.0
• Tokenizers 0.21.1