59 lines
1.8 KiB
Markdown
59 lines
1.8 KiB
Markdown
> 🧩This is a template for code README.md accompanying a Machine Learning paper
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# My owesome paper title
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This repository is the official implementation of [My owesome paper title](https://arxiv.org/abs/2030.12345).
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> 🧩Optional: include a graphic explaining your approach or main result.
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## Requirements
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To install requirements:
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```
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pip install -r requirements.txt
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```
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> 🧩Describe how to set up the environment, e.g. pip/conda/docker commands, download datasets, etc...
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## Training
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To train the model in the paper, run this command:
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```
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python train.py --input-data <path_to_data> --alpha 10 --beta 20
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```
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> 👉Describe how to train the model, with example commands on how to train the models in your paper, including the full training procedure and hyperparameter optimisation approach.
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## Evaluation
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To evaluate my model on ImageNet, run:
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```
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python eval.py --model-file mymodel.pth --benchmark imagenet
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```
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> 🧩Describe how to evaluate the trained models on benchmarks reported in the paper, give example commands.
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## Pre-trained models
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We provide links to pretrained models:
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- [mymodel.pth](https://drive.google.com/filehash)
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> 🧩Give a link to where/how the pretrained models can be downloaded and used (if applicable).
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## Results
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Our model achieves the following performance on :
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- [Image Classification on ImageNet](https://paperswithcode.com/sota/image-classification-on-imagenet)
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| Model name | Top 1 Accuracy | Top 5 Accuracy |
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| --------------- |---------------- | -------------- |
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| My model | 85% | 95% |
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> 🧩Include a table of results from your paper, and link back to the leaderboard to give readers more context in the future. If your main result is a figure, include that figure and link to the command or notebook to reproduce it.
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