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mmcgovern574
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distilhubert-finetuned-gtzan

Audio Classification
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hubert
Generated from Trainer
Eval Results (legacy)
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  1. README.md +26 -26
  2. model.safetensors +1 -1
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: 0.77
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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: 0.7536
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- - Accuracy: 0.77
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  ## Model description
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@@ -52,9 +52,9 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 2e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
@@ -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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- | 2.2844 | 1.0 | 57 | 2.2655 | 0.24 |
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- | 2.1199 | 2.0 | 114 | 2.0507 | 0.48 |
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- | 1.7662 | 3.0 | 171 | 1.7611 | 0.56 |
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- | 1.5841 | 4.0 | 228 | 1.5132 | 0.68 |
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- | 1.3824 | 5.0 | 285 | 1.3399 | 0.67 |
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- | 1.2609 | 6.0 | 342 | 1.2268 | 0.72 |
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- | 1.0785 | 7.0 | 399 | 1.1935 | 0.7 |
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- | 1.0587 | 8.0 | 456 | 1.0674 | 0.7 |
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- | 0.9831 | 9.0 | 513 | 0.9904 | 0.74 |
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- | 0.9783 | 10.0 | 570 | 0.9502 | 0.73 |
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- | 0.829 | 11.0 | 627 | 0.9090 | 0.76 |
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- | 0.7314 | 12.0 | 684 | 0.8753 | 0.74 |
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- | 0.6674 | 13.0 | 741 | 0.8584 | 0.76 |
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- | 0.8236 | 14.0 | 798 | 0.8069 | 0.78 |
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- | 0.6861 | 15.0 | 855 | 0.7878 | 0.77 |
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- | 0.6585 | 16.0 | 912 | 0.7773 | 0.76 |
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- | 0.5389 | 17.0 | 969 | 0.7695 | 0.78 |
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- | 0.6257 | 18.0 | 1026 | 0.7907 | 0.76 |
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- | 0.546 | 19.0 | 1083 | 0.7648 | 0.77 |
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- | 0.6432 | 20.0 | 1140 | 0.7536 | 0.77 |
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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: 0.88
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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: 0.8080
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+ - Accuracy: 0.88
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.7263 | 1.0 | 113 | 1.6331 | 0.59 |
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+ | 1.1167 | 2.0 | 226 | 1.2046 | 0.65 |
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+ | 0.774 | 3.0 | 339 | 0.8365 | 0.8 |
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+ | 0.6507 | 4.0 | 452 | 0.7015 | 0.81 |
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+ | 0.5046 | 5.0 | 565 | 0.6722 | 0.81 |
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+ | 0.2632 | 6.0 | 678 | 0.6743 | 0.82 |
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+ | 0.203 | 7.0 | 791 | 0.7351 | 0.84 |
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+ | 0.0902 | 8.0 | 904 | 0.5898 | 0.86 |
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+ | 0.0215 | 9.0 | 1017 | 0.6213 | 0.87 |
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+ | 0.0097 | 10.0 | 1130 | 0.6948 | 0.86 |
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+ | 0.1171 | 11.0 | 1243 | 0.6228 | 0.87 |
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+ | 0.0054 | 12.0 | 1356 | 0.7101 | 0.86 |
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+ | 0.0035 | 13.0 | 1469 | 0.7626 | 0.87 |
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+ | 0.0028 | 14.0 | 1582 | 0.7659 | 0.86 |
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+ | 0.0027 | 15.0 | 1695 | 0.6993 | 0.87 |
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+ | 0.0023 | 16.0 | 1808 | 0.7345 | 0.87 |
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+ | 0.0023 | 17.0 | 1921 | 0.8363 | 0.86 |
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+ | 0.0018 | 18.0 | 2034 | 0.7779 | 0.88 |
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+ | 0.0018 | 19.0 | 2147 | 0.8275 | 0.87 |
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+ | 0.0018 | 20.0 | 2260 | 0.8080 | 0.88 |
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  ### Framework versions
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