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Gwenn-LR
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distilhubert-finetuned-gtzan

Audio Classification
Transformers
Safetensors
hubert
Generated from Trainer
Eval Results
Inference Endpoints
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End of training

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  1. README.md +23 -23
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -23,7 +23,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.83
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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 +33,8 @@ 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: 1.0006
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- - Accuracy: 0.83
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  ## Model description
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@@ -66,26 +66,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 2.1596 | 1.0 | 113 | 2.0536 | 0.57 |
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- | 1.3991 | 2.0 | 226 | 1.4396 | 0.62 |
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- | 1.1572 | 3.0 | 339 | 1.1858 | 0.72 |
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- | 0.7911 | 4.0 | 452 | 0.9571 | 0.74 |
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- | 0.6416 | 5.0 | 565 | 0.8319 | 0.76 |
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- | 0.5359 | 6.0 | 678 | 0.7642 | 0.77 |
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- | 0.4587 | 7.0 | 791 | 0.5897 | 0.82 |
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- | 0.1906 | 8.0 | 904 | 0.7896 | 0.76 |
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- | 0.3607 | 9.0 | 1017 | 0.6474 | 0.78 |
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- | 0.1783 | 10.0 | 1130 | 0.6477 | 0.82 |
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- | 0.065 | 11.0 | 1243 | 0.5573 | 0.84 |
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- | 0.1105 | 12.0 | 1356 | 0.7545 | 0.85 |
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- | 0.0193 | 13.0 | 1469 | 0.7586 | 0.85 |
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- | 0.0114 | 14.0 | 1582 | 0.7817 | 0.81 |
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- | 0.0204 | 15.0 | 1695 | 0.8912 | 0.84 |
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- | 0.0059 | 16.0 | 1808 | 0.9070 | 0.84 |
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- | 0.004 | 17.0 | 1921 | 1.1039 | 0.81 |
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- | 0.0031 | 18.0 | 2034 | 0.6472 | 0.88 |
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- | 0.0023 | 19.0 | 2147 | 1.1127 | 0.82 |
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- | 0.0023 | 20.0 | 2260 | 1.0006 | 0.83 |
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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: 0.9692
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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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+ | 2.1424 | 1.0 | 113 | 2.0512 | 0.42 |
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+ | 1.3894 | 2.0 | 226 | 1.4091 | 0.64 |
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+ | 1.1928 | 3.0 | 339 | 1.0341 | 0.65 |
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+ | 0.7863 | 4.0 | 452 | 0.8563 | 0.74 |
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+ | 0.5829 | 5.0 | 565 | 0.7003 | 0.79 |
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+ | 0.5068 | 6.0 | 678 | 0.6707 | 0.84 |
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+ | 0.585 | 7.0 | 791 | 0.6079 | 0.86 |
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+ | 0.2768 | 8.0 | 904 | 0.5873 | 0.82 |
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+ | 0.2623 | 9.0 | 1017 | 0.5571 | 0.85 |
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+ | 0.1195 | 10.0 | 1130 | 0.5802 | 0.88 |
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+ | 0.0979 | 11.0 | 1243 | 0.5688 | 0.85 |
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+ | 0.1958 | 12.0 | 1356 | 0.7861 | 0.81 |
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+ | 0.0541 | 13.0 | 1469 | 0.8633 | 0.77 |
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+ | 0.0222 | 14.0 | 1582 | 0.7360 | 0.83 |
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+ | 0.0115 | 15.0 | 1695 | 0.6911 | 0.82 |
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+ | 0.0118 | 16.0 | 1808 | 0.9468 | 0.8 |
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+ | 0.0355 | 17.0 | 1921 | 1.0997 | 0.8 |
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+ | 0.0033 | 18.0 | 2034 | 0.9888 | 0.78 |
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+ | 0.0026 | 19.0 | 2147 | 0.9846 | 0.83 |
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+ | 0.0027 | 20.0 | 2260 | 0.9692 | 0.82 |
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  ### Framework versions
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