BERT_Offensive_English_Twitter

This model is a fine-tuned version of bert-large-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.2731
• Macro F1: 0.8890
• Micro F1: 0.8954
• Accuracy: 0.8954

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: 8
• eval_batch_size: 10
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Macro F1	Micro F1	Accuracy
0.3321	1.0	4036	0.6479	0.5302	0.5589	0.5589
0.4337	2.0	8073	0.3772	0.8346	0.8524	0.8524
0.2945	3.0	12109	0.3232	0.8753	0.8843	0.8843
0.243	4.0	16144	0.2731	0.8890	0.8954	0.8954

Framework versions

• Transformers 4.27.1
• Pytorch 2.0.1+cu118
• Datasets 2.9.0
• Tokenizers 0.13.3