Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Trained with AutoTrain
text-embeddings-inference
Instructions to use connork0/20epoch10batch2grad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connork0/20epoch10batch2grad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connork0/20epoch10batch2grad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connork0/20epoch10batch2grad") model = AutoModelForSequenceClassification.from_pretrained("connork0/20epoch10batch2grad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 2.805943489074707
f1_macro: 0.4598130841121495
f1_micro: 0.5462962962962963
f1_weighted: 0.4629629629629629
precision_macro: 0.42289719626168226
precision_micro: 0.5462962962962963
precision_weighted: 0.4251543209876543
recall_macro: 0.5420560747663551
recall_micro: 0.5462962962962963
recall_weighted: 0.5462962962962963
accuracy: 0.5462962962962963
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Model tree for connork0/20epoch10batch2grad
Base model
distilbert/distilbert-base-uncased