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--- |
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base_model: cardiffnlp/twitter-xlm-roberta-base-sentiment |
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metrics: |
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- accuracy |
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model-index: |
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- name: result |
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results: [] |
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language: |
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- ar |
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- en |
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library_name: transformers |
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pipeline_tag: text-classification |
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--- |
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--- |
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# SentimentArEng |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.502831 |
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- Accuracy: 0.798512 |
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# inference with pipeline |
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``` |
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from transformers import pipeline |
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model_path = "Noor0/SentimentArEng" |
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sentiment_task = pipeline("sentiment-analysis", model=model_path, tokenizer=model_path) |
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sentiment_task("ุชุนุงู
ู ุงูู
ูุธููู ูุงู ุฃูู ู
ู ุงูู
ุชููุน") |
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``` |
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- output: |
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- [{'label': 'negative', 'score': 0.9905518293380737}] |
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## Training and evaluation data |
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- Training set: 114,885 records |
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- evaluation data: 12,765 records |
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## Training procedure |
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| Training Loss | Epoch |Validation Loss | Accuracy | |
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|:-------------:|:-----:|:---------------:|:--------:| |
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| 0.4511 | 2.0 |0.502831 | 0.7985 | |
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| 0.3655 | 3.0 |0.576118 | 0.7954 | |
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| 0.3019 | 4.0 |0.625391 | 0.7985 | |
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| 0.2466 | 5.0 |0.835689 | 0.7979 | |
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### Training hyperparameters |
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- The following hyperparameters were used during training: |
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- learning_rate=2e-5 |
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- num_train_epochs=20 |
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- weight_decay=0.01 |
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- batch_size=16, |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.11.0 |
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- Tokenizers 0.14.1 |
