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---
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title: HTK
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app_file: app1.py
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sdk: gradio
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sdk_version: 4.36.1
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---
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# MRC-RetroReader
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## Introduction
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MRC-RetroReader is a machine reading comprehension (MRC) model designed for reading comprehension tasks. The model leverages advanced neural network architectures to provide high accuracy in understanding and responding to textual queries.
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## Table of Contents
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- [Introduction](#introduction)
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- [Table of Contents](#table-of-contents)
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- [Installation](#installation)
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- [Usage](#usage)
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- [Features](#features)
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- [Dependencies](#dependencies)
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- [Configuration](#configuration)
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- [Documentation](#documentation)
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- [Examples](#examples)
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- [Troubleshooting](#troubleshooting)
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- [Contributors](#contributors)
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- [License](#license)
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## Installation
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1. Clone the repository:
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```
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git clone https://github.com/phanhoang1803/MRC-RetroReader.git
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cd MRC-RetroReader
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```
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2. Install the required dependencies:
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```
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pip install -r requirements.txt
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```
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## Usage
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- For notebooks: to running automatically, turn off wandb, warning if necessary:
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```
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wandb off
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import warnings
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warnings.filterwarnings('ignore')
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```
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- To train the model using the SQuAD v2 dataset:
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```
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python train_squad_v2.py --config path-to-yaml-file --module intensive --batch_size batch_size
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```
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## Features
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- High accuracy MRC model
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- Easy to train on custom datasets
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- Configurable parameters for model tuning
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## Dependencies
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- Python 3.x
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- PyTorch
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- Transformers
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- Tokenizers
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For a full list of dependencies, see `requirements.txt`.
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## Configuration
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Configuration files can be found in the `configs` directory. Adjust the parameters in these files to customize the model training and evaluation.
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## Documentation
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For detailed documentation, refer to the `documentation` directory. This includes:
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- Model architecture
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- Training procedures
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- Evaluation metrics
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## Examples
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Example training and evaluation scripts are provided in the repository. To train on the SQuAD v2 dataset:
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## Troubleshooting
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For common issues and their solutions, refer to the `troubleshooting guide`.
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## Contributors
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- phanhoang1803
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## License
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This project is licensed under the MIT License. See the `LICENSE` file for details.
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