Text Classification
Transformers
Safetensors
Arabic
bert
arabic
toxicity
hate-speech
cyberbullying
content-moderation
offensive-language
profanity
multi-dialect
arabic-nlp
MARBERTv2
Eval Results (legacy)
text-embeddings-inference
Instructions to use youssefreda9/HAYAA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use youssefreda9/HAYAA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="youssefreda9/HAYAA")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("youssefreda9/HAYAA") model = AutoModelForSequenceClassification.from_pretrained("youssefreda9/HAYAA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model": "training/best_model", | |
| "train_rows": 30967, | |
| "val_rows": 3441, | |
| "epochs_completed": 3.0, | |
| "best_f1": 0.8512281251502576, | |
| "training_time_hours": 0.2599656800429026, | |
| "class_weights": [ | |
| 1.0, | |
| 2.8849579726508594 | |
| ], | |
| "hyperparameters": { | |
| "max_length": 128, | |
| "batch_size": 16, | |
| "gradient_accumulation": 2, | |
| "learning_rate": 5e-06, | |
| "warmup_ratio": 0.1, | |
| "weight_decay": 0.01, | |
| "fp16": true, | |
| "seed": 42 | |
| } | |
| } |