veeresh11/workout-activity-classifier

Model Card for Model ID

Fine-tuned DistilBERT classifying workout effort from text descriptions

Model Details

Model Description

• Developed by: Veeresh R G
• Model type: Classification
• Language(s) (NLP): English
• License: Apache 2.0
• Finetuned from model [optional]: DistilBertForSequenceClassification

Uses

The fine-tuned model is intended to be used to classify a workout based on the description and provide a further suggestion as to what should be done next. For example, after a really hard workout, the model recommends to take some days off or do some kind of active recovery

[More Information Needed]

Bias, Risks, and Limitations

Sometime the description of the workout may not reflect the true nature of the workout. It can be misleading, which results in wrong classification and the incorrect recovery suggestions. For example, an activity having a average HR of 185 and above is a very hard workout, but if the title says "Easy Workout" then the model can suggest another threshold workout the next day. This is a correct but wrong in the overall context The model demands a valid, cleaned dataset for it to perform well

Recommendations

Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

How to Get Started with the Model

Use the code below to get started with the model.

[More Information Needed]

Training Details

Training Data

Synthetically generated data for training. The training data consists of activity description of the physical activity recorded by a wearable

Training Procedure

Used Distil-Bert as the base model to help classify the activity based on the classification. The model uses the [CLS] token to indicate the classification task. The model classifies the activity as Hard / Moderate / Easy level based on the description of the activity