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distilhubert-finetuned-gtzan

Audio Classification
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hubert
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  1. README.md +18 -18
  2. model.safetensors +1 -1
  3. runs/Dec28_14-13-02_Billapati-Home/events.out.tfevents.1703752998.Billapati-Home.877.0 +2 -2
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.84
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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
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [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: 1.2778
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- - Accuracy: 0.84
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  ## Model description
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@@ -66,21 +66,21 @@ 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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- | 0.0061 | 1.0 | 113 | 0.9999 | 0.84 |
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- | 0.0735 | 2.0 | 226 | 1.2200 | 0.78 |
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- | 0.2103 | 3.0 | 339 | 1.6617 | 0.74 |
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- | 0.0075 | 4.0 | 452 | 1.5453 | 0.75 |
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- | 0.0004 | 5.0 | 565 | 1.3464 | 0.84 |
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- | 0.0006 | 6.0 | 678 | 1.3242 | 0.81 |
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- | 0.0246 | 7.0 | 791 | 1.7457 | 0.76 |
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- | 0.0003 | 8.0 | 904 | 1.2888 | 0.82 |
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- | 0.0002 | 9.0 | 1017 | 1.1534 | 0.83 |
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- | 0.0011 | 10.0 | 1130 | 1.1696 | 0.85 |
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- | 0.1217 | 11.0 | 1243 | 1.1479 | 0.83 |
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- | 0.0002 | 12.0 | 1356 | 1.4423 | 0.84 |
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- | 0.0002 | 13.0 | 1469 | 1.2385 | 0.84 |
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- | 0.0002 | 14.0 | 1582 | 1.2497 | 0.85 |
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- | 0.0002 | 15.0 | 1695 | 1.2778 | 0.84 |
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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: 0.83
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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
 
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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: 0.9983
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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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+ | 2.0454 | 1.0 | 113 | 1.9653 | 0.56 |
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+ | 1.3054 | 2.0 | 226 | 1.3132 | 0.7 |
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+ | 0.9479 | 3.0 | 339 | 0.9596 | 0.75 |
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+ | 0.7291 | 4.0 | 452 | 0.8110 | 0.75 |
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+ | 0.6033 | 5.0 | 565 | 0.7330 | 0.81 |
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+ | 0.2973 | 6.0 | 678 | 0.7070 | 0.79 |
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+ | 0.3574 | 7.0 | 791 | 0.6908 | 0.83 |
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+ | 0.2078 | 8.0 | 904 | 0.7105 | 0.83 |
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+ | 0.1569 | 9.0 | 1017 | 0.7204 | 0.83 |
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+ | 0.0812 | 10.0 | 1130 | 0.7471 | 0.84 |
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+ | 0.0451 | 11.0 | 1243 | 0.8439 | 0.85 |
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+ | 0.0148 | 12.0 | 1356 | 0.9538 | 0.83 |
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+ | 0.0096 | 13.0 | 1469 | 0.9364 | 0.84 |
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+ | 0.0084 | 14.0 | 1582 | 0.9808 | 0.83 |
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+ | 0.0084 | 15.0 | 1695 | 0.9983 | 0.83 |
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  ### Framework versions
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