AIKIA_0.6_OFFENSIVE_BERT_MULTILINGUAL

<!-- 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. -->

AIKIA_0.6_OFFENSIVE_BERT_MULTILINGUAL

This model is a fine-tuned version of bert-base-multilingual-uncased on the AIKIA Greek dataset with 0.6 threshold for the Offensive label. It achieves the following results on the evaluation set:

• Loss: 1.5183
• Macro F1: 0.6983
• Micro F1: 0.7565
• Accuracy: 0.7565

Results on test set:

• Accuracy: 0.7784313725490196

• F1 score: 0.7575514222182127

• Precision: 0.7545776520467404

• Recall : 0.7612935323383084

• Matthews Correlation Coefficient: 0.5158274671154518

• Precision of each class: [0.84188912 0.66726619]

• Recall of each class: [0.8159204 0.70666667]

• F1 score of each class: [0.82870136 0.68640148]

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: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 10

Training results

Framework versions

• Transformers 4.30.2
• Pytorch 2.0.1+cu118
• Datasets 2.13.1
• Tokenizers 0.13.3