metadata
license: apache-2.0
language:
- en
baseline: facebook_BART
pipeline_tag: text-classification
tags:
- mobile_application
- user_reviews
widget:
- text: >-
I can see the intentions behind this app but the execution feels very much
lackluster. The quizzes are full of grammar errors and the questions feel
very surface level. The quizzes also seem to be aimed at current short
term issues versus establishing a baseline and working on keeping track of
daily changes. I just see how helpful the app would be to someone to use
everyday if there is no baseline established.
example_title: Example 1
- text: >-
The 'affirmations' are not like the ones advertised. Possibly just AI
made... But I don't know. Plus it says 'in app purchases' but it isn't
stated that you have to pay for the app. Not worth it. Not even worth
keeping for the entire 3 day trial. Sorry. I gave it an extra star because
at least it looks pretty and I liked that you could (sort of) schedule
when the affirmations arrived. It is a lovely idea but I don't feel it
stuck the landing and I definitely don't want to pay for it.
example_title: Example 2
- text: >-
I want to like and use this app. However, it's extremely buggy. It just
displayed a loading spinner for 3 minutes before finally opening. The
app's busy spinner is the same as their logo, which is appropriate -
you'll see that spinner a lot. Also, the UI is a strange mixture of
polished yet confusing. Everything looks nice, but I still have a hard
time navigating around. All that said, the mindfulness meditation
exercises leave me feeling fantastic. They make the app worthwhile to me.
example_title: Example 3
- text: >-
I just experienced biofeedback therapy and learned that I don't breathe
from my diaphragm most of the time. In looking for a guided breathing app,
I finally discovered this simple gem. You just breathe with the ball as it
expands and releases at a gentle pace. The pace is adjustable. I'm not
there yet but I can feel and breathe the difference in a few sessions. The
developer's response to a minor question was answered literally overnight:
I wrote at 1 a.m. and had an answer by 8 a.m.. This guided breathing app
would be great for people who, like me, don't like meditation guides with
somber voices, or struggle with simple belly breathing.
example_title: Example 4
Model Name
Model Description
This multi-label classification model is a fine-tuned version of Facebook's BART model specifically tailored for analyzing mobile application user reviews. It can classify reviews into 38 distinct classes, covering various aspects like usability, functionality, pricing, and more. This model aims to assist developers and marketers in gaining insights from user feedback efficiently.
Model Details
- Architecture: The model is based on the BART (Bidirectional and Auto-Regressive Transformers) architecture, renowned for its effectiveness in natural language understanding tasks.
- Training Data: Fine-tuned on a dataset comprising user reviews from multiple mobile applications, collected from various app stores. The dataset includes over 4k user reviews categorized into 38 classes.
- Training Procedure: The model was trained using a multi-label classification approach, with a focus on maximizing the accuracy across all categories. Training involved adjusting the learning rate and using a batch size optimized for GPU capabilities.
Example Usage
from transformers import AutoModel, AutoTokenizer
model = AutoModel.from_pretrained("merqsous/mBart")
tokenizer = AutoTokenizer.from_pretrained("merqsous/mBart")
inputs = tokenizer("Example input text here", return_tensors="pt")
outputs = model(**inputs)