Intro
OpenDiffusion's SentimentCheck is an AI model built upon Tensorflow+Keras+Pickles. SentimentCheck harnesses the power of deep learning algorithms to accurately classify sentiment in text, making it a flexible tool for businesses, researchers, and developers.
Usage
language:
- en
- nl
- de
- fr
- it
- es
license: mit
bert-base-multilingual-uncased-sentiment
This a bert-base-multilingual-uncased model finetuned for sentiment analysis on product reviews in six languages: English, Dutch, German, French, Spanish and Italian. It predicts the sentiment of the review as a number of stars (between 1 and 5).
This model is intended for direct use as a sentiment analysis model for product reviews in any of the six languages above, or for further finetuning on related sentiment analysis tasks.
Training data
Here is the number of product reviews we used for finetuning the model:
| Language | Number of reviews |
|---|---|
| English | 150k |
| Dutch | 80k |
| German | 137k |
| French | 140k |
| Italian | 72k |
| Spanish | 50k |
Accuracy
The finetuned model obtained the following accuracy on 5,000 held-out product reviews in each of the languages:
- Accuracy (exact) is the exact match on the number of stars.
- Accuracy (off-by-1) is the percentage of reviews where the number of stars the model predicts differs by a maximum of 1 from the number given by the human reviewer.
| Language | Accuracy (exact) | Accuracy (off-by-1) |
|---|---|---|
| English | 67% | 95% |
| Dutch | 57% | 93% |
| German | 61% | 94% |
| French | 59% | 94% |
| Italian | 59% | 95% |
| Spanish | 58% | 95% |