Model Card for Model ID
The base model is llama-3-smaug 8b llm . smaug is suffix used by abacusai that trains llms using DPO strategy
The final model is the base model finetuned using LORA technique on entity-level-sentiment-analysis data. How does the data look : { 'text' : "Ashley was seen with suspects before the day of crime. Witnesses say that Ashley knew about the crime beforehand. Police are searching her home in pursuance of evidences. Ashley's parents, Ron and Maria are renowned business people of the town who are known for their charity works.", 'entity': "Ashley", 'label': 'Negative'}
Model Details
Open source model that can be used to determine sentiment analysis of a person or company that is mentioned in say, a newspaper article.
Model Description
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Final model finetuned by: rajiv-data-chef
- Funded by [optional]: rajiv-data-chef
- Shared by [optional]: rajiv-data-chef
- Model type: llama-3-smaug-8b
- Language(s) (NLP): [More Information Needed]
- License: [More Information Needed]
- Finetuned from model [optional]: abacusai/Llama-3-Smaug-8B
Model Sources [optional]
- Repository: [More Information Needed]
- Paper [optional]: [More Information Needed]
- Demo [optional]: [More Information Needed]
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]
Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type: [More Information Needed]
- Hours used: [More Information Needed]
- Cloud Provider: [More Information Needed]
- Compute Region: [More Information Needed]
- Carbon Emitted: [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]
- Downloads last month
- 11