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--- |
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base_model: aubmindlab/bert-base-arabertv02 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- offenseval_2020 |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: ArabertHateSpeech |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: offenseval_2020 |
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type: offenseval_2020 |
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config: ar |
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split: test |
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args: ar |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9425287356321839 |
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- name: F1 |
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type: f1 |
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value: 0.8543689320388349 |
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- name: Precision |
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type: precision |
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value: 0.875 |
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- name: Recall |
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type: recall |
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value: 0.8346883468834688 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# ArabertHateSpeech |
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This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the offenseval_2020 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2500 |
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- Accuracy: 0.9425 |
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- F1: 0.8544 |
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- Precision: 0.875 |
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- Recall: 0.8347 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 12 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| No log | 1.0 | 490 | 0.1377 | 0.9321 | 0.8263 | 0.8551 | 0.7995 | |
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| 0.1418 | 2.0 | 980 | 0.0967 | 0.9321 | 0.8121 | 0.9210 | 0.7263 | |
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| 0.0898 | 3.0 | 1470 | 0.1082 | 0.9442 | 0.8517 | 0.9185 | 0.7940 | |
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| 0.0595 | 4.0 | 1960 | 0.1530 | 0.9338 | 0.8358 | 0.8370 | 0.8347 | |
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| 0.0405 | 5.0 | 2450 | 0.1559 | 0.9442 | 0.8579 | 0.8825 | 0.8347 | |
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| 0.0194 | 6.0 | 2940 | 0.2175 | 0.9398 | 0.8541 | 0.8364 | 0.8726 | |
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| 0.0153 | 7.0 | 3430 | 0.1994 | 0.9392 | 0.8452 | 0.8707 | 0.8211 | |
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| 0.0102 | 8.0 | 3920 | 0.2154 | 0.9403 | 0.8541 | 0.8439 | 0.8645 | |
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| 0.0093 | 9.0 | 4410 | 0.2296 | 0.9409 | 0.8470 | 0.8872 | 0.8103 | |
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| 0.0047 | 10.0 | 4900 | 0.2406 | 0.9420 | 0.8524 | 0.8768 | 0.8293 | |
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| 0.0038 | 11.0 | 5390 | 0.2530 | 0.9436 | 0.8591 | 0.8674 | 0.8509 | |
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| 0.0051 | 12.0 | 5880 | 0.2500 | 0.9425 | 0.8544 | 0.875 | 0.8347 | |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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