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Anastasia07
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distilhubert-finetuned-gtzan

Audio Classification
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hubert
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End of training

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  1. README.md +13 -13
  2. model.safetensors +1 -1
README.md CHANGED
@@ -20,7 +20,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.85
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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
@@ -30,8 +30,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5827
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- - Accuracy: 0.85
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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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- | 1.9384 | 1.0 | 113 | 1.8194 | 0.51 |
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- | 1.1592 | 2.0 | 226 | 1.2633 | 0.65 |
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- | 1.0055 | 3.0 | 339 | 0.9778 | 0.69 |
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- | 0.6643 | 4.0 | 452 | 0.8497 | 0.72 |
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- | 0.5357 | 5.0 | 565 | 0.6839 | 0.78 |
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- | 0.2881 | 6.0 | 678 | 0.5971 | 0.81 |
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- | 0.3532 | 7.0 | 791 | 0.6110 | 0.8 |
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- | 0.138 | 8.0 | 904 | 0.6072 | 0.82 |
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- | 0.201 | 9.0 | 1017 | 0.6156 | 0.85 |
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- | 0.088 | 10.0 | 1130 | 0.5827 | 0.85 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.82
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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 [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5975
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+ - Accuracy: 0.82
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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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+ | 1.9623 | 1.0 | 113 | 1.8760 | 0.41 |
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+ | 1.1752 | 2.0 | 226 | 1.2402 | 0.64 |
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+ | 1.0548 | 3.0 | 339 | 0.9436 | 0.78 |
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+ | 0.6057 | 4.0 | 452 | 0.7890 | 0.79 |
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+ | 0.4924 | 5.0 | 565 | 0.6666 | 0.82 |
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+ | 0.2522 | 6.0 | 678 | 0.5841 | 0.84 |
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+ | 0.1771 | 7.0 | 791 | 0.5813 | 0.8 |
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+ | 0.0977 | 8.0 | 904 | 0.6138 | 0.81 |
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+ | 0.1059 | 9.0 | 1017 | 0.5675 | 0.82 |
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+ | 0.0687 | 10.0 | 1130 | 0.5975 | 0.82 |
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  ### Framework versions
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