Text Classification
Transformers
Safetensors
roberta
Trained with AutoTrain
text-embeddings-inference
Instructions to use smend0/autotrain-jsfrv-ectej with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smend0/autotrain-jsfrv-ectej with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="smend0/autotrain-jsfrv-ectej")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("smend0/autotrain-jsfrv-ectej") model = AutoModelForSequenceClassification.from_pretrained("smend0/autotrain-jsfrv-ectej", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Text Classification This model was a test to use Hugging Face's AutoTrain feature and fine tune a bert model. It was trained using the IMDB dataset.
Validation Metrics
loss: 0.37337836623191833
f1: 0.8897659994361432
precision: 0.8392129055132069
recall: 0.9468
auc: 0.95721034
accuracy: 0.8827
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