---
library_name: transformers
tags: []
---

# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->



## Model Details

### Model Description

<!-- Provide a longer summary of what this model is. -->

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

- **Developed by:** [Jinha Kim and Jerry Chen]
- **Model type:** [LLM Prompt Classifier]
- **License:** [MIT]
- **Finetuned from model [distilgpt2]:** [https://huggingface.co/distilbert/distilgpt2]

<!-- Provide the basic links for the model. -->

- **Repository:** [https://huggingface.co/jkim03/rendezvous-radar-model]

## Uses

Used to return OpenStreetMap tags from user prompts.


### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

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

## Training Details

### Training Data

[Training data](https://github.com/rendezvous-radar/RendezvousRadar/blob/main/backend/prompt_training.csv)

### Training Procedure and Hyperparameters

[Training Script](https://github.com/rendezvous-radar/RendezvousRadar/blob/main/backend/backend/prediction/inference.py)

#### Speeds, Sizes, Times [optional]

Training runtime: 774.4637
Training samples per second: 1.704
Training steps per second: 0.857

## Evaluation

Training Loss: 1.234485605394984
Epoch: 8.0
Loss: 0.3482