Text Classification
Transformers
TensorBoard
Safetensors
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use nathanh2020/bert-tweet-country-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nathanh2020/bert-tweet-country-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nathanh2020/bert-tweet-country-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nathanh2020/bert-tweet-country-classifier") model = AutoModelForSequenceClassification.from_pretrained("nathanh2020/bert-tweet-country-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 1.7039090394973755
f1_macro: 0.26440768430871364
f1_micro: 0.6123426703096263
f1_weighted: 0.5814494747640245
precision_macro: 0.4240941570326134
precision_micro: 0.6123426703096263
precision_weighted: 0.6080611005322797
recall_macro: 0.23297120205125718
recall_micro: 0.6123426703096263
recall_weighted: 0.6123426703096263
accuracy: 0.6123426703096263
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Model tree for nathanh2020/bert-tweet-country-classifier
Base model
google-bert/bert-base-multilingual-uncased