Text Classification
Transformers
TensorBoard
Safetensors
Persian
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use papooabedini/testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use papooabedini/testing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="papooabedini/testing")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("papooabedini/testing") model = AutoModelForSequenceClassification.from_pretrained("papooabedini/testing", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 0.07203829288482666
f1_macro: 0.988301685943485
f1_micro: 0.9868173258003766
f1_weighted: 0.9867815660378358
precision_macro: 0.9884888715707831
precision_micro: 0.9868173258003766
precision_weighted: 0.9869930752212238
recall_macro: 0.9883333333333333
recall_micro: 0.9868173258003766
recall_weighted: 0.9868173258003766
accuracy: 0.9868173258003766
- Downloads last month
- -
Model tree for papooabedini/testing
Base model
HooshvareLab/bert-fa-base-uncased