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--- |
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license: cc-by-nc-4.0 |
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datasets: |
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- Veucci/lyric-to-3genre |
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language: |
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- en |
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library_name: transformers |
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tags: |
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- music |
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widget: |
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- text: >- |
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When I'm away from you, I'm happier than ever Wish I could explain it better |
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I wish it wasn't true Give me a day or two to think of something clever To |
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write myself a letter To tell me what to do, mm-mmm Do you read my |
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interviews? Or do you skip my avenue? (My avenue) When you (when you) said |
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you were passing through Was I even on your way? I knew when I asked you to |
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(when I asked you to) Be cool about what I was telling you You'd do the |
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opposite of what you said you'd do (what you said you'd do) And I'd end up |
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more afraid Don't say it isn't fair You clearly weren't aware that you made |
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me miserable So if you really wanna know |
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example_title: (Pop) Happier Than Ever - Billie Eilish |
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- text: >- |
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Look, I was gonna go easy on you and not to hurt your feelings But I'm only |
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going to get this one chance (six minutes, six minutes) Something's wrong, I |
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can feel it (six minutes, six minutes, Slim Shady, you're on) Just a feeling |
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I've got, like something's about to happen, but I don't know what If that |
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means what I think it means, we're in trouble, big trouble And if he is as |
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bananas as you say, I'm not taking any chances You are just what the doctor |
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ordered I'm beginning to feel like a Rap God, Rap God All my people from the |
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front to the back nod, back nod Now who thinks their arms are long enough to |
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slap box, slap box? They said I rap like a robot, so call me Rapbot |
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example_title: (Hip-Hop) Rap God - Eminem |
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- text: >- |
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Come as you are, as you were As I want you to be As a friend, as a friend As |
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an old enemy Take your time, hurry up Choice is yours, don't be late Take a |
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rest as a friend As an old Memoria, memoria Memoria, memoria Come doused in |
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mud, soaked in bleach As I want you to be As a trend, as a friend As an old |
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Memoria, memoria Memoria, memoria |
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example_title: (Rock) Come as You Are - Nirvana |
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--- |
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# Lyrics Genre Classification Model |
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## Description |
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The model was trained using the BERT language model on my [song lyrics dataset](https://huggingface.co/datasets/Veucci/lyrics_3genre) to predict the genre of a given song based on its lyrics. This repository houses the machine learning model, which is capable of making predictions in three distinct genres: Pop, Rock, and Hip-Hop. |
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For training and test codes check out [Github page](https://github.com/Veucci/lyrics-to-genre-lite). |
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## Dataset |
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The model was trained on a diverse and labeled dataset of song lyrics, which contained approximately 3000 rows. The dataset was carefully curated to include songs from a wide range of artists and genres, ensuring a comprehensive representation of Pop, Rock, and Hip-Hop music. |
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[DATASET](https://huggingface.co/datasets/Veucci/lyrics_3genre) |
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## Quick Start |
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```py |
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from transformers import pipeline |
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classifier = pipeline("text-classification", model="Veucci/lyrics-to-genre") |
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result = classifier("When I'm away from you, I'm happier than ever Wish I could explain it better I wish it wasn't true") |
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print(result) |
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``` |
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## License |
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This dataset is released under the Creative Commons Attribution-NonCommercial license. This means that you are not allowed to use the dataset for commercial purposes. For detailed information about the license, please refer to the [LICENSE](./LICENSE) file. |
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## Contact |
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If you have any questions, suggestions, or concerns regarding this dataset, please feel free to reach out to email at [[email protected]](mailto:[email protected]). |
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I hope this model helps in your genre classification tasks and inspires further exploration of song lyrics analysis! |
