Testing csv data in fine-tuned model for text classification

I am a newbie and still learning GPT-3. I got a dataset that contains two columns: text and labels of the text. A label can have two values i.e. 1 or 0. It’s text classification problem. I am trying to do the fine-tuning of the model. I split the dataset into training (i.e. 14000 rows) and testing (6000 rows) datasets. I used the following command to turn training dataset CSV file into JSON:
openai tools fine_tunes.prepare_data -f "Path of csv file"

Then I ran the command to upload the JSON file and to choose the model
openai api fine_tines_create -t "path to json file" --model ada

The model was created when I ran the above command. Now I want to test my testing dataset. In the examples, it was shown how to test a couple of sentences by using the following command:

openai api completions.create -m model_name -p prompt_value

I could not figure out how can I send the testing dataset (which is saved in CSV format) in the above command. Should I first convert into JSON format using the first command and then enter the path of the converted JSON file as a prompt parameter? Or is there any other way? Any help would be really appreciated. Thanks

Hi there! Did you try these steps? OpenAI API