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% |
Contact
In addition to this model, NLP Town offers custom, monolingual sentiment models for many languages and an improved multilingual model through RapidAPI.
Feel free to contact us for questions, feedback and/or requests for similar models.
数据统计
数据评估
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