Update README.md
#13
by
rajKisHor
- opened
README.md
CHANGED
@@ -12,9 +12,9 @@ license: mit
|
|
12 |
|
13 |
# bert-base-multilingual-uncased-sentiment
|
14 |
|
15 |
-
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).
|
16 |
|
17 |
-
This model is intended for direct use as a sentiment analysis model for product reviews in any of the six languages above
|
18 |
|
19 |
## Training data
|
20 |
|
@@ -31,9 +31,9 @@ Here is the number of product reviews we used for finetuning the model:
|
|
31 |
|
32 |
## Accuracy
|
33 |
|
34 |
-
The
|
35 |
|
36 |
-
- Accuracy (exact) is the exact match
|
37 |
- 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.
|
38 |
|
39 |
|
|
|
12 |
|
13 |
# bert-base-multilingual-uncased-sentiment
|
14 |
|
15 |
+
This is 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).
|
16 |
|
17 |
+
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.
|
18 |
|
19 |
## Training data
|
20 |
|
|
|
31 |
|
32 |
## Accuracy
|
33 |
|
34 |
+
The fine-tuned model obtained the following accuracy on 5,000 held-out product reviews in each of the languages:
|
35 |
|
36 |
+
- Accuracy (exact) is the exact match for the number of stars.
|
37 |
- 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.
|
38 |
|
39 |
|