Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Trained with AutoTrain
text-embeddings-inference
Instructions to use hthadicherla/actsa-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hthadicherla/actsa-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hthadicherla/actsa-distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hthadicherla/actsa-distilbert") model = AutoModelForSequenceClassification.from_pretrained("hthadicherla/actsa-distilbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model Trained Using AutoTrain
- Problem type: Text Classification
Validation Metrics
loss: 1.0657285451889038
f1_macro: 0.2095479509928179
f1_micro: 0.4584103512014787
f1_weighted: 0.2881768494245037
precision_macro: 0.1528034504004929
precision_micro: 0.4584103512014787
precision_weighted: 0.21014005008866307
recall_macro: 0.3333333333333333
recall_micro: 0.4584103512014787
recall_weighted: 0.4584103512014787
accuracy: 0.4584103512014787
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