| --- |
| base_model: cardiffnlp/twitter-xlm-roberta-base-sentiment |
| metrics: |
| - accuracy |
| model-index: |
| - name: result |
| results: [] |
| language: |
| - ar |
| - en |
| library_name: transformers |
| pipeline_tag: text-classification |
| --- |
| --- |
|
|
| # SentimentArEng |
|
|
| This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment](https://huggingface.co/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("ุชุนุงู
ู ุงูู
ูุธููู ูุงู ุฃูู ู
ู ุงูู
ุชููุน") |
| |
| ``` |
|
|
| - 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 |
