| # Fine-tuned XLM-R Model for hebrew Sentiment Analysis | |
| This is a fine-tuned XLM-R model for sentiment analysis in hebrew. | |
| ## Model Details | |
| - **Model Name**: XLM-R Sentiment Analysis | |
| - **Language**: hebrew | |
| - **Fine-tuning Dataset**: DGurgurov/hebrew_sa | |
| ## Training Details | |
| - **Epochs**: 20 | |
| - **Batch Size**: 32 (train), 64 (eval) | |
| - **Optimizer**: AdamW | |
| - **Learning Rate**: 5e-5 | |
| ## Performance Metrics | |
| - **Accuracy**: 0.92106 | |
| - **Macro F1**: 0.90782 | |
| - **Micro F1**: 0.92106 | |
| ## Usage | |
| To use this model, you can load it with the Hugging Face Transformers library: | |
| ```python | |
| from transformers import AutoTokenizer, AutoModelForSequenceClassification | |
| tokenizer = AutoTokenizer.from_pretrained("DGurgurov/xlm-r_hebrew_sentiment") | |
| model = AutoModelForSequenceClassification.from_pretrained("DGurgurov/xlm-r_hebrew_sentiment") | |
| ``` | |
| ## License | |
| [MIT] | |