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Current progress on evaluation module. See readme & documentation for usage.
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# Evaluation
This module contains utilities and scripts for empirical, numerical evaluation of model outputs. Much of the code written in this module is guided by methodologies described in [this paper](https://staff.aist.go.jp/m.goto/PAPER/TIEICE202309watanabe.pdf) (Watanabe, 2023).
### Data formatting
Using the [evaluate_model.py](evaluate_model.py) script, evaluation can be run on an existing `json` database of outputs. Database must contain a list of song containers in the following format:
```json
[
{ // container for song 1
"id": (int) ...,
"prompt": (str) ..., //optional
"model_response": (str) ...,
"target_response": (str) ... //optional
},
{ // container for song 2
"id": (int) ..., // unique from song 1
"prompt": (str) ..., //optional
"model_response": (str) ...,
"target_response": (str) ... //optional
},
.
.
.
]
```
### Quick start
Run the following script to quick start an evaluation:
```bash
py evaluation/evaluate_model.py <path_to_your_database>
```
To run different measures, consider passing in a list of measures into the `--measures` argument:
```bash
py evaluation/evaluate_model.py <path_to_your_database> --measures diversity meter syllable
```