amharic-hate-speech

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amharic-hate-speech

This model is a fine-tuned version of uhhlt/am-roberta on an AmahricHateSpeechRANL dataset. It achieves the following results on the evaluation set:

• Loss: 0.6437
• Accuracy: 0.7373
• Precision: 0.7216
• Recall: 0.7149
• F1: 0.7180

How to use it

from transformers import pipeline
amhate_classifier = pipeline("text-classification", model="uhhlt/amharic-hate-speech")
amhate_classifier(["🌳☘️ 🌳☘️ለልጅ ልጅ የሚተላለፍ ዘመን ተሻጋሪ ኢንቨስትመንት !!!🌳☘️ 🌳☘️።", 
                  "አንተ አሁን ምን የሚሉህ ነህ? ግኡዝ አምላኪ ከመሆን ያድነን። ሰውን ያክል ፍጡር እየሞተ ለዛፍ ይሄን ያክል ማምለክ ጤነኝነት አይመስልም ። ፋኖ 100% ያሸንፋል",
                  "በአናትህ ተተከል ባንዳ ተላላኪ"])

Output

[{'label': 'normal', 'score': 0.8840981721878052},
 {'label': 'hate', 'score': 0.519339382648468},
 {'label': 'hate', 'score': 0.9630571007728577}]

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
• train_batch_size: 128
• eval_batch_size: 128
• seed: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 8

Training results

Framework versions

• Transformers 4.32.1
• Pytorch 2.0.1+cu117
• Datasets 2.14.4
• Tokenizers 0.13.3