|
--- |
|
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 |
