README.md

metadata

base_model: aubmindlab/bert-base-arabertv02
tags:
  - generated_from_trainer
datasets:
  - offenseval_2020
metrics:
  - accuracy
model-index:
  - name: ArabertHateSpeech
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: offenseval_2020
          type: offenseval_2020
          config: ar
          split: test
          args: ar
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9255610290093049

ArabertHateSpeech

This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on the offenseval_2020 dataset. It achieves the following results on the evaluation set:

• Loss: 0.3259
• Accuracy: 0.9256

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1895	1.0	980	0.4345	0.9206
0.1472	2.0	1960	0.3537	0.9228
0.1365	3.0	2940	0.3259	0.9256

Framework versions

• Transformers 4.33.1
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3