Annotator_1_Mi

Annotator_1_Mi

Overview

Annotator_1_Mi is the First LLM for semantic tabular data annotation

Model Details

Model Description

Annotator_1_Mi is a Decoder-based LM fine-tuned from Mistravl-7B-v0.1

• Developed by: tsotsa
• Model type: Decoder
• Language(s) (NLP): Semantic annotation for tabular data
• License: Apache 2.0
• Finetuned from model: Mistravl-7B-v0.1

Licence

Annotator_1_Mi is developed under Apache 2.0 licence

Uses

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Direct Use

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Downstream Use [optional]

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Out-of-Scope Use

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Bias, Risks, and Limitations

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Recommendations

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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.

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Training Details

Training Data

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Training Procedure

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Preprocessing [optional]

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Training Hyperparameters

• Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

Speeds, Sizes, Times [optional]

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Evaluation

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Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

• Recall
• Precision
• F1 Score

Results

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Summary

Model Examination [optional]

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Environmental Impact

bon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

• Environment: Google collab
• GPU Type: T4 with 15 Go
• Hours used: 100.4 min

Model Architecture and Objective

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Compute Infrastructure

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Hardware

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Software

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BibTeX:

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APA:

Model Card Contact

tsotsa

Framework versions

• PEFT 0.8.2