Text Classification
Transformers
ONNX
Safetensors
English
distilbert
intent-classification
multitask
iab
conversational-ai
adtech
calibrated-confidence
text-embeddings-inference
Instructions to use admesh/agentic-intent-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use admesh/agentic-intent-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="admesh/agentic-intent-classifier")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("admesh/agentic-intent-classifier", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,213 Bytes
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"head": "multitask_intent",
"loss_weights": {
"decision_phase": 1.0,
"intent_subtype": 1.0,
"intent_type": 1.0
},
"test_count": 70,
"test_metrics": {
"epoch": 4.0,
"test_decision_phase_accuracy": 0.7586206896551724,
"test_decision_phase_macro_f1": 0.763718820861678,
"test_intent_subtype_accuracy": 0.8714285714285714,
"test_intent_subtype_macro_f1": 0.8317236029317956,
"test_intent_type_accuracy": 0.8723404255319149,
"test_intent_type_macro_f1": 0.8005555555555555,
"test_loss": 1.4344456195831299,
"test_runtime": 0.1682,
"test_samples_per_second": 416.197,
"test_steps_per_second": 29.728
},
"train_count": 1590,
"val_count": 473,
"val_metrics": {
"epoch": 4.0,
"val_decision_phase_accuracy": 0.9560975609756097,
"val_decision_phase_macro_f1": 0.9496568779026763,
"val_intent_subtype_accuracy": 0.8950617283950617,
"val_intent_subtype_macro_f1": 0.8822267346328656,
"val_intent_type_accuracy": 0.9757785467128027,
"val_intent_type_macro_f1": 0.970010435450997,
"val_loss": 0.5456064343452454,
"val_runtime": 1.1168,
"val_samples_per_second": 423.544,
"val_steps_per_second": 26.863
}
}
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