toxiBERT_v1

This model is a fine-tuned version of philschmid/tiny-bert-sst2-distilled on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2924
• Accuracy: 0.8901
• F1 Binary: 0.7643
• Precision: 0.6946
• Recall: 0.8496
• Roc Auc: 0.9505

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Use 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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Binary	Precision	Recall	Roc Auc
0.4005	1.0	2062	0.3620	0.8571	0.6993	0.6259	0.7924	0.9196
0.3372	2.0	4124	0.3213	0.8668	0.7265	0.6381	0.8433	0.9374
0.3157	3.0	6186	0.3061	0.8807	0.7473	0.6721	0.8415	0.9439
0.3148	4.0	8248	0.3019	0.8859	0.7569	0.6839	0.8473	0.9466
0.3093	5.0	10310	0.3026	0.8898	0.7616	0.6967	0.8398	0.9473

Framework versions

• Transformers 4.57.6
• Pytorch 2.9.1+cpu
• Datasets 4.4.2
• Tokenizers 0.22.1