wetey/MARBERT-LHSAB

This model is part of the work done in <!-- add paper name -->. <br> The full code can be found at https://github.com/wetey/cluster-errors

Model Details

Model Description

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• —Model type: BERT-based
• —Language(s) (NLP): Arabic
• —Finetuned from model: UBC-NLP/MARBERT

How to Get Started with the Model

Use the code below to get started with the model.

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-classification", model="wetey/MARBERT-LHSAB")

# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("wetey/MARBERT-LHSAB")
model = AutoModelForSequenceClassification.from_pretrained("wetey/MARBERT-LHSAB")

Fine-tuning Details

Fine-tuning Data

This model is fine-tuned on the L-HSAB. The exact version we use (after removing duplicates) can be found [](). <!--TODO-->

Fine-tuning Procedure

The exact fine-tuning procedure followed can be found here

Training Hyperparameters

evaluationstrategy = 'epoch' loggingsteps = 1, numtrainepochs = 5, learningrate = 1e-5, evalaccumulation_steps = 2

Evaluation

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Testing Data

Test set used can be found here

Results

accuracy: 87.9% <br> precision: 88.1% <br> recall: 87.9% <br> f1-score: 87.9% <br>

#### Results per class | Label | Precision | Recall | F1-score| |---------|---------|---------|---------| | normal | 85% | 82% | 83% | | abusive | 93% | 92% | 93% | | hate | 68% | 78% | 72% |

Citation

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