# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("daccuong2002/PhoBert-MultiLabel")
model = AutoModelForSequenceClassification.from_pretrained("daccuong2002/PhoBert-MultiLabel", device_map="auto")Quick Links
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 0.24498265981674194
f1_macro: 0.9244631728799089
f1_micro: 0.9390389672483863
f1_weighted: 0.9389134636561386
precision_macro: 0.9458913396195016
precision_micro: 0.9390389672483863
precision_weighted: 0.9393976940878069
recall_macro: 0.9051122705051101
recall_micro: 0.9390389672483863
recall_weighted: 0.9390389672483863
accuracy: 0.9390389672483863
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Model tree for daccuong2002/PhoBert-MultiLabel
Base model
vinai/phobert-base-v2
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="daccuong2002/PhoBert-MultiLabel")