Anul 3 Semestrul 1

Anul 3/Semestrul 1/Proiect Colectiv/StoryPointEstimator/README.md

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+# Story Point Estimator
+
+This repository contains code for training and evaluating and exporting models for story point estimation.
+
+The dataset used for training is the [IEEE TSE2018 dataset](https://github.com/jai2shukla/JIRA-Estimation-Prediction/tree/master/storypoint/IEEE%20TSE2018/dataset) which contains user stories from 16 open-source projects from 9 different organizations.
+
+
+Currently, the following models are supported:
+- [x] [DistilBERT](https://arxiv.org/abs/1910.01108)
+
+
+## Setup
+
+#### Create and activate conda environment
+
+```bash
+conda create --name spestimator python=3.8
+conda activate spestimator
+```
+
+#### Install dependencies
+
+```bash
+pip install torch==2.4.1 --index-url https://download.pytorch.org/whl/cu124
+pip install -r requirements.txt
+```
+
+#### Setup dotenv
+
+Create a `.env` file in the root directory and add the following environment variables:
+
+```bash
+DATA_PATH=<path to data directory>
+```
+
+
+## Usage
+
+#### Train models for story point estimation
+
+See training options
+
+```bash
+python train.py --help
+```
+
+Train a model with your desired options while also seing validation results
+
+```bash
+python train.py <options>
+```
+
+Users can see in the experiments folder the results inside a subfolder with their experiment's name. The folder contains: <br>
+        - a checkpoints folder where the results of each epoch and their according performance metrics are stored <br>
+        - a params.json file with the experiment's parameters <br>
+        - a log file with the experiment's logs regarding the training process <br>
+
+
+#### Evaluate existing models
+
+See evaluation options
+
+```bash
+python eval.py --help
+```
+
+Evaluate a model with your desired options
+
+```bash
+python eval.py <options>
+```
+
+
+#### Export models
+
+See export options
+
+```bash
+python export.py --help
+```
+
+Export a model with your desired options
+
+```bash
+python export.py <options>
+```
+
+Exports the model and tokenizer to the specified directory. The <b>model</b> is stored in a <b>.safetensors</b> file (for python users) and an <b>.onnx</b> file for other languages, and the <b>tokenizer</b> is stored in a <b>vocab.txt</b> file and 4 json files: <b>config.json, special_tokens_map.json, tokenizer_config.json, and tokenizer.json</b>.