# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Safouene/OpenB_snetiement_analysis_test")
model = AutoModelForSequenceClassification.from_pretrained("Safouene/OpenB_snetiement_analysis_test")Quick Links
flaubert sentiment
This is a flaubert model finetuned for sentiment analysis on company emails in French. It predicts the sentiment of the email, from negative to positive.
This model is intended for direct use as a sentiment analysis model for French emails, or for further finetuning on related sentiment analysis tasks.
Training data
The training data consists of the French portion of emails_multi, supplemented with another 40,000 similar emails.
Accuracy
The finetuned model was evaluated on the French test set of emails_multi.
- 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) |
|---|---|
| French | 95% |
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Safouene/OpenB_snetiement_analysis_test")