metadata

language:
  - en
license: mit
library_name: mlflow
tags:
  - intent-classification
  - text-classification
  - mlflow
datasets:
  - custom
metrics:
  loss: 1.0714781284332275
  epoch: 2
model-index:
  - name: Intent Classification Model
    results:
      - task:
          type: text-classification
          subtype: intent-classification
        metrics:
          - type: loss
            value: 1.0714781284332275
          - type: epoch
            value: 2

Intent Classification Model

This is an intent classification model trained using MLflow and uploaded to the Hugging Face Hub.

Model Details

Model Type: Intent Classification
Framework: MLflow
Run ID: ebe2ca3ecb634a96bf1ea3f65b2f86b9

Training Details

Parameters

num_epochs: '2'
model_name: distilbert-base-uncased
learning_rate: 5e-05
early_stopping_patience: None
weight_decay: '0.01'
batch_size: '32'
max_length: '128'
num_labels: '3'

Metrics

loss: 1.0714781284332275
epoch: 2.0

Usage

This model can be used to classify intents in text. It was trained using MLflow and can be loaded using the MLflow model registry.

Loading the Model

import mlflow

# Load the model
model = mlflow.pyfunc.load_model("runs:/ebe2ca3ecb634a96bf1ea3f65b2f86b9/intent_model")

# Make predictions
text = "your text here"
prediction = model.predict([{"text": text}])

Additional Information

For more information about using this model or the training process, please refer to the repository documentation.