kmack commited on
Commit
87d9d01
·
verified ·
1 Parent(s): f246f1e

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +4 -4
README.md CHANGED
@@ -16,18 +16,18 @@ tags:
16
  ---
17
  # Yelp Review Classifier
18
 
19
- This model is a sentiment classification model for Yelp reviews, trained to predict whether a review is **positive** or **negative**. The model was fine-tuned using the `distilbert-base-uncased` model architecture, based on the [DistilBERT model](https://huggingface.co/distilbert/distilbert-base-uncased) from Hugging Face, and trained on a Yelp reviews dataset.
20
 
21
  ## Model Details
22
  - **Model Type**: DistilBERT-based model for sequence classification
23
  - **Model Architecture**: `distilbert-base-uncased`
24
  - **Number of Parameters**: Approximately 66M parameters
25
- - **Training Dataset**: The model was trained on a curated Yelp reviews dataset, labeled for sentiment (positive/negative).
26
- - **Fine-Tuning Task**: Sentiment analysis for Yelp reviews (positive or negative sentiment)
27
 
28
  ## Training Data
29
  - **Dataset**: Custom Yelp reviews dataset
30
- - **Data Description**: The dataset consists of Yelp reviews, each labeled with a sentiment (positive/negative).
31
  - **Preprocessing**: The dataset was preprocessed by cleaning the reviews to remove unwanted characters and URLs.
32
 
33
  ## Training Details
 
16
  ---
17
  # Yelp Review Classifier
18
 
19
+ This model is a sentiment classification model for Yelp reviews, trained to predict whether a review is **star ratings (1 to 5 stars)**. The model was fine-tuned using the `distilbert-base-uncased` model architecture, based on the [DistilBERT model](https://huggingface.co/distilbert/distilbert-base-uncased) from Hugging Face, and trained on a Yelp reviews dataset.
20
 
21
  ## Model Details
22
  - **Model Type**: DistilBERT-based model for sequence classification
23
  - **Model Architecture**: `distilbert-base-uncased`
24
  - **Number of Parameters**: Approximately 66M parameters
25
+ - **Training Dataset**: The model was trained on a curated Yelp reviews dataset, labeled for star ratings (1 to 5 stars).
26
+ - **Fine-Tuning Task**: Multi-class classification for Yelp reviews, predicting the star rating (from 1 to 5 stars) based on the content of the review.
27
 
28
  ## Training Data
29
  - **Dataset**: Custom Yelp reviews dataset
30
+ - **Data Description**: The dataset consists of Yelp reviews, labeled for star ratings (1 to 5 stars).
31
  - **Preprocessing**: The dataset was preprocessed by cleaning the reviews to remove unwanted characters and URLs.
32
 
33
  ## Training Details