Model Card for ACARISBERT-DistilBERT
A 3-class DistilBERT model finetuned on 300k rows of labeled Discord messages, Twitter posts, and Reddit comments (refs soon).
Classes: ["pos", "neg", "neu"].
Model Details
Model Description
An encoder-only sentiment analysis model finetuned to classify text sequences into three sentiment classes: "pos", "neg", and "neu".
- Developed by: OngakkenAI
- Model type: DistilBertForSequenceClassification (modified for multiclass)
- Language(s) (NLP): en
- License: Proprietary (while running eval and testing)
- Finetuned from model: DistilBERT
Uses
Direct Use
[More Information Needed]
Downstream Use [optional]
[More Information Needed]
Out-of-Scope Use
[More Information Needed]
Bias, Risks, and Limitations
[More Information Needed]
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
[More Information Needed]
Training Procedure
Preprocessing [optional]
[More Information Needed]
Training Hyperparameters
- Training regime: [More Information Needed]
Speeds, Sizes, Times [optional]
[More Information Needed]
Evaluation
Testing Data, Factors & Metrics
Testing Data
[More Information Needed]
Factors
[More Information Needed]
Metrics
[More Information Needed]
Results
[More Information Needed]
Summary
Model Examination [optional]
[More Information Needed]
Technical Specifications [optional]
Model Architecture and Objective
[More Information Needed]
Compute Infrastructure
[More Information Needed]
Hardware
[More Information Needed]
Software
[More Information Needed]
Citation [optional]
BibTeX:
[More Information Needed]
APA:
[More Information Needed]
Glossary [optional]
[More Information Needed]
More Information [optional]
[More Information Needed]
Model Card Authors [optional]
[More Information Needed]
Model Card Contact
[More Information Needed]
