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SentimentArEng

This model is a fine-tuned version of cardiffnlp/twitter-xlm-roberta-base-sentiment on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.502831
• Accuracy: 0.798512

inference with pipeline

from transformers import pipeline
model_path = "Noor0/SentimentArEng"
sentiment_task = pipeline("sentiment-analysis", model=model_path, tokenizer=model_path)
sentiment_task("تعامل الموظفين كان أقل من المتوقع")

• output:
• [{'label': 'negative', 'score': 0.9905518293380737}]

Training and evaluation data

• Training set: 114,885 records
• evaluation data: 12,765 records

Training procedure

Training Loss	Epoch	Validation Loss	Accuracy
0.4511	2.0	0.502831	0.7985
0.3655	3.0	0.576118	0.7954
0.3019	4.0	0.625391	0.7985
0.2466	5.0	0.835689	0.7979

Training hyperparameters

• The following hyperparameters were used during training:
  • learning_rate=2e-5
  • num_train_epochs=20
  • weight_decay=0.01
  • batch_size=16,

Framework versions

• Transformers 4.35.0
• Pytorch 2.0.0
• Datasets 2.11.0
• Tokenizers 0.14.1