
# BERT-AJGT
Arabic version bert model fine tuned on AJGT dataset

## Data
The model were fine-tuned on ~1800 sentence from twitter for Jordanian dialect.


## Results
| class    | precision | recall | f1-score | Support |
|----------|-----------|--------|----------|---------|
| 0        | 0.9462    | 0.9778 | 0.9617   | 90    |
| 1        | 0.9399    | 0.9689 | 0.9542   | 90    |
| Accuracy |           |        | 0.9611   | 180   |



## 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-ajgt"
model = AutoModelForSequenceClassification.from_pretrained(model_name,num_labels=2)
tokenizer = AutoTokenizer.from_pretrained(model_name)

```

{"language": ["ar"], "tags": ["AJGT"], "datasets": ["AJGT"], "widget": [{"text": "\u064a\u0647\u062f\u064a \u0627\u0644\u0644\u0647 \u0645\u0646 \u064a\u0634\u0627\u0621"}, {"text": "\u0627\u0644\u0627\u0633\u0644\u0648\u0628 \u0642\u0630\u0631 \u0648\u0642\u0645\u0627\u0645\u0647"}]}
transformers pytorch bert text-classification AJGT ar dataset:AJGT autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #AJGT #ar #dataset-AJGT #autotrain_compatible #endpoints_compatible #region-us 

BERT-AJGT
=========


Arabic version bert model fine tuned on AJGT dataset


Data
----


The model were fine-tuned on ~1800 sentence from twitter for Jordanian dialect.


Results
-------



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:



TAGS
#transformers #pytorch #bert #text-classification #AJGT #ar #dataset-AJGT #autotrain_compatible #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #bert #text-classification #AJGT #ar #dataset-AJGT #autotrain_compatible #endpoints_compatible #region-us 
