Text Classification
Transformers
TensorBoard
Safetensors
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use skgswamy/autotrain-ast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use skgswamy/autotrain-ast with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="skgswamy/autotrain-ast")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("skgswamy/autotrain-ast") model = AutoModelForSequenceClassification.from_pretrained("skgswamy/autotrain-ast", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 0.6366264820098877
f1_macro: 0.7281242357544632
f1_micro: 0.7333333333333333
f1_weighted: 0.7281242357544632
precision_macro: 0.7401515151515152
precision_micro: 0.7333333333333333
precision_weighted: 0.7401515151515152
recall_macro: 0.7333333333333334
recall_micro: 0.7333333333333333
recall_weighted: 0.7333333333333333
accuracy: 0.7333333333333333
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Model tree for skgswamy/autotrain-ast
Base model
google-bert/bert-base-uncased