Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Trained with AutoTrain
text-embeddings-inference
Instructions to use ghosh100/hcde560-autotrain-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghosh100/hcde560-autotrain-text-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ghosh100/hcde560-autotrain-text-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ghosh100/hcde560-autotrain-text-classification") model = AutoModelForSequenceClassification.from_pretrained("ghosh100/hcde560-autotrain-text-classification") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 0.3647119700908661
f1_macro: 0.914141414141414
f1_micro: 0.9142857142857143
f1_weighted: 0.9141774891774891
precision_macro: 0.9163492063492064
precision_micro: 0.9142857142857143
precision_weighted: 0.9163537414965987
recall_macro: 0.9142512077294686
recall_micro: 0.9142857142857143
recall_weighted: 0.9142857142857143
accuracy: 0.9142857142857143
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Model tree for ghosh100/hcde560-autotrain-text-classification
Base model
typeform/distilbert-base-uncased-mnli