christinacdl/AIKIA_0.6_OFFENSIVE_BERT_MULTILINGUAL

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AIKIA0.6OFFENSIVEBERTMULTILINGUAL

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
• —trainbatchsize: 16
• —evalbatchsize: 16
• —seed: 42
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —lrschedulerwarmup_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