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update with context

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  1. README.md +10 -7
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  ---
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  license: apache-2.0
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  tags:
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- - generated_from_trainer
 
 
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  datasets:
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  - marsyas/gtzan
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  metrics:
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  model-index:
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  - name: distilhubert-finetuned-gtzan_accuracy_93
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  results: []
 
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,26 +20,25 @@ should probably proofread and complete it, then remove this comment. -->
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  # distilhubert-finetuned-gtzan_accuracy_93
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- This model is a fine-tuned version of [yuval6967/distilhubert-finetuned-gtzan](https://huggingface.co/yuval6967/distilhubert-finetuned-gtzan) on the GTZAN dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.5121
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  - __Accuracy: 0.93__
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  ## Model description
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- Fine-tuned model to demonstrate > 87% accuracy for the Huggingface Audio course
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  ## Intended uses & limitations
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- - Example fine-tuned model for HF Audio course credit
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  ## Training and evaluation data
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  More information needed
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  ## Training procedure
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- - a non-standard split of 0.20 for test_size was used
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- - this model is built on top of an existing model [yuval6967/distilhubert-finetuned-gtzan] that had an accuracy of 87% from
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  ### Training hyperparameters
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  - Transformers 4.30.2
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.13.1
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- - Tokenizers 0.13.3
 
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  ---
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  license: apache-2.0
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  tags:
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+ - music
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+ - genre
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+ - classification
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  datasets:
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  - marsyas/gtzan
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  metrics:
 
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  model-index:
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  - name: distilhubert-finetuned-gtzan_accuracy_93
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  results: []
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+ language:
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+ - en
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  # distilhubert-finetuned-gtzan_accuracy_93
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+ ### This model is a fine-tuned version of [yuval6967/distilhubert-finetuned-gtzan](https://huggingface.co/yuval6967/distilhubert-finetuned-gtzan) on the GTZAN dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.5121
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  - __Accuracy: 0.93__
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  ## Model description
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+ - Fine-tuned model to demonstrate > 87% accuracy for the [Huggingface Audio course](https://huggingface.co/learn/audio-course/chapter0/introduction)
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  ## Intended uses & limitations
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+ - Model is built to identify the genre of music based on a ~30 sec clip
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  ## Training and evaluation data
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  More information needed
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  ## Training procedure
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+ - test_size = 0.20 was used for the split
 
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  ### Training hyperparameters
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  - Transformers 4.30.2
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.13.1
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+ - Tokenizers 0.13.3