File size: 1,189 Bytes
5bc10cb e85a608 5bc10cb e85a608 5bc10cb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 |
---
language:
- ar
datasets:
- ArSentD-LEV
tags:
- ArSentD-LEV
widget:
- text: "يهدي الله من يشاء"
- text: "الاسلوب قذر وقمامه"
---
# bert-arsentd-lev
Arabic version bert model fine tuned on ArSentD-LEV dataset
## Data
The model were fine-tuned on ~4000 sentence from twitter multiple dialect and five classes we used 3 out of 5 int the experiment.
## Results
| class | precision | recall | f1-score | Support |
|----------|-----------|--------|----------|---------|
| 0 | 0.8211 | 0.8080 | 0.8145 | 125 |
| 1 | 0.7174 | 0.7857 | 0.7500 | 84 |
| 2 | 0.6867 | 0.6404 | 0.6628 | 89 |
| Accuracy | | | 0.7517 | 298 |
## How to use
You can use these models by installing `torch` or `tensorflow` and Huggingface library `transformers`. And you can use it directly by initializing it like this:
```python
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model_name="mofawzy/bert-arsentd-lev"
model = AutoModelForSequenceClassification.from_pretrained(model_name,num_labels=3)
tokenizer = AutoTokenizer.from_pretrained(model_name)
```
|