Is it necessary to re-train BERT models, specifically RoBERTa model?

0

Issue

I am looking for a sentiment analysis code with atleast 80%+ accuracy. I tried Vader and it I found it easy and usable, however it was giving accuracy of 64% only.

Now, I was looking at some BERT models and I noticed it needs to be re-trained? Is that correct? Isn’t it pre-trained? is re-training necessary?

Solution

You can use pre-trained models from HuggingFace. There are plenty to choose from. Search for emotion or sentiment models

Here is an example of a model with 26 emotions. The current implementation works but is very slow for large datasets.

import pandas as pd
from transformers import RobertaTokenizerFast, TFRobertaForSequenceClassification, pipeline

tokenizer = RobertaTokenizerFast.from_pretrained("arpanghoshal/EmoRoBERTa")
model = TFRobertaForSequenceClassification.from_pretrained("arpanghoshal/EmoRoBERTa")


emotion = pipeline('sentiment-analysis', 
                    model='arpanghoshal/EmoRoBERTa')

# example data
DATA_URI = "https://github.com/AFAgarap/ecommerce-reviews-analysis/raw/master/Womens%20Clothing%20E-Commerce%20Reviews.csv"
dataf = pd.read_csv(DATA_URI, usecols=["Review Text",])

# This is super slow, I will find a better optimization ASAP


dataf = (dataf
         .head(50) # comment this out for the whole dataset
         .assign(Emotion = lambda d: (d["Review Text"]
                                       .fillna("")
                                       .map(lambda x: emotion(x)[0].get("label", None))
                                  ),
             
            )
)

We could also refactor it a bit

...
# a bit faster than the previous but still slow

def emotion_func(text:str) -> str:
    if not text:
        return None
    return emotion(text)[0].get("label", None)
    



dataf = (dataf
         .head(50) # comment this out for the whole dataset
         .assign(Emotion = lambda d: (d["Review Text"]
                                        .map(emotion_func)
                                     ),

            )
)

Results:

    Review Text Emotion
0   Absolutely wonderful - silky and sexy and comf...   admiration
1   Love this dress! it's sooo pretty. i happene... love
2   I had such high hopes for this dress and reall...   fear
3   I love, love, love this jumpsuit. it's fun, fl...   love
...
6   I aded this in my basket at hte last mintue to...   admiration
7   I ordered this in carbon for store pick up, an...   neutral
8   I love this dress. i usually get an xs but it ...   love
9   I'm 5"5' and 125 lbs. i ordered the s petite t...   love
...
16  Material and color is nice. the leg opening i...    neutral
17  Took a chance on this blouse and so glad i did...   admiration
...
26  I have been waiting for this sweater coat to s...   excitement
27  The colors weren't what i expected either. the...   disapproval
...
31  I never would have given these pants a second ...   love
32  These pants are even better in person. the onl...   disapproval
33  I ordered this 3 months ago, and it finally ca...   disappointment
34  This is such a neat dress. the color is great ...   admiration
35  Wouldn't have given them a second look but tri...   love
36  This is a comfortable skirt that can span seas...   approval
...
40  Pretty and unique. great with jeans or i have ...   admiration
41  This is a beautiful top. it's unique and not s...   admiration
42  This poncho is so cute i love the plaid check ...   love
43  First, this is thermal ,so naturally i didn't ...   love

Answered By – Prayson W. Daniel

This Answer collected from stackoverflow, is licensed under cc by-sa 2.5 , cc by-sa 3.0 and cc by-sa 4.0

Leave A Reply

Your email address will not be published.

This website uses cookies to improve your experience. We'll assume you're ok with this, but you can opt-out if you wish. Accept Read More