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wav2vec2-base-finetuned-gtzan-finetuned-gtzan

Audio Classification
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Safetensors
wav2vec2
Generated from Trainer
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  1. README.md +11 -16
  2. model.safetensors +1 -1
README.md CHANGED
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  ---
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- library_name: transformers
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  license: apache-2.0
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  base_model: yuval6967/wav2vec2-base-finetuned-gtzan
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  tags:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.83
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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
@@ -33,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [yuval6967/wav2vec2-base-finetuned-gtzan](https://huggingface.co/yuval6967/wav2vec2-base-finetuned-gtzan) on the GTZAN dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1628
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- - Accuracy: 0.83
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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- | 0.2026 | 0.9956 | 112 | 1.2365 | 0.78 |
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- | 0.3141 | 2.0 | 225 | 1.0698 | 0.8 |
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- | 0.0457 | 2.9956 | 337 | 0.9390 | 0.84 |
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- | 0.1295 | 4.0 | 450 | 1.1925 | 0.82 |
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- | 0.0108 | 4.9956 | 562 | 0.9958 | 0.86 |
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- | 0.1734 | 6.0 | 675 | 1.5863 | 0.75 |
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- | 0.0067 | 6.9956 | 787 | 0.9112 | 0.85 |
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- | 0.2115 | 8.0 | 900 | 1.0695 | 0.83 |
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- | 0.0061 | 8.9956 | 1012 | 1.1494 | 0.82 |
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- | 0.0038 | 9.9556 | 1120 | 1.1628 | 0.83 |
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  ### Framework versions
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- - Transformers 4.45.0.dev0
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- - Pytorch 2.3.1+cu121
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  - Datasets 2.21.0
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  - Tokenizers 0.19.1
 
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  ---
 
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  license: apache-2.0
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  base_model: yuval6967/wav2vec2-base-finetuned-gtzan
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  tags:
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.78
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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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  This model is a fine-tuned version of [yuval6967/wav2vec2-base-finetuned-gtzan](https://huggingface.co/yuval6967/wav2vec2-base-finetuned-gtzan) on the GTZAN dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.3065
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+ - Accuracy: 0.78
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 0.6708 | 0.9956 | 112 | 1.2056 | 0.75 |
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+ | 0.6752 | 2.0 | 225 | 1.1245 | 0.78 |
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+ | 0.1894 | 2.9956 | 337 | 1.0640 | 0.81 |
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+ | 0.2192 | 4.0 | 450 | 1.3034 | 0.76 |
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+ | 0.2675 | 4.9956 | 562 | 1.0633 | 0.81 |
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+ | 0.1237 | 6.0 | 675 | 1.3065 | 0.78 |
 
 
 
 
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  ### Framework versions
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+ - Transformers 4.44.0
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+ - Pytorch 2.4.0
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  - Datasets 2.21.0
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  - Tokenizers 0.19.1
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