metadata

base_model: aubmindlab/bert-base-arabertv02
tags:
  - generated_from_trainer
datasets:
  - offenseval_2020
metrics:
  - accuracy
  - f1
  - precision
  - recall
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: 0.9425287356321839
          - name: F1
            type: f1
            value: 0.8543689320388349
          - name: Precision
            type: precision
            value: 0.875
          - name: Recall
            type: recall
            value: 0.8346883468834688

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: 0.2500
Accuracy: 0.9425
F1: 0.8544
Precision: 0.875
Recall: 0.8347

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 12

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
No log	1.0	490	0.1377	0.9321	0.8263	0.8551	0.7995
0.1418	2.0	980	0.0967	0.9321	0.8121	0.9210	0.7263
0.0898	3.0	1470	0.1082	0.9442	0.8517	0.9185	0.7940
0.0595	4.0	1960	0.1530	0.9338	0.8358	0.8370	0.8347
0.0405	5.0	2450	0.1559	0.9442	0.8579	0.8825	0.8347
0.0194	6.0	2940	0.2175	0.9398	0.8541	0.8364	0.8726
0.0153	7.0	3430	0.1994	0.9392	0.8452	0.8707	0.8211
0.0102	8.0	3920	0.2154	0.9403	0.8541	0.8439	0.8645
0.0093	9.0	4410	0.2296	0.9409	0.8470	0.8872	0.8103
0.0047	10.0	4900	0.2406	0.9420	0.8524	0.8768	0.8293
0.0038	11.0	5390	0.2530	0.9436	0.8591	0.8674	0.8509
0.0051	12.0	5880	0.2500	0.9425	0.8544	0.875	0.8347

Framework versions

Transformers 4.33.1
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3