Text Classification
Transformers
TensorBoard
Safetensors
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use rohithsappa/autotrain-ast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rohithsappa/autotrain-ast with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rohithsappa/autotrain-ast")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rohithsappa/autotrain-ast") model = AutoModelForSequenceClassification.from_pretrained("rohithsappa/autotrain-ast", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 0.6531299948692322
f1_macro: 0.7418704794672465
f1_micro: 0.7466666666666667
f1_weighted: 0.7418704794672466
precision_macro: 0.7507665945165946
precision_micro: 0.7466666666666667
precision_weighted: 0.7507665945165946
recall_macro: 0.7466666666666666
recall_micro: 0.7466666666666667
recall_weighted: 0.7466666666666667
accuracy: 0.7466666666666667
- Downloads last month
- 3
Model tree for rohithsappa/autotrain-ast
Base model
google-bert/bert-base-uncased