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HamzaSidhu786
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distilhubert-finetuned-gtzan

Audio Classification
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wav2vec2
Generated from Trainer
Eval Results
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HamzaSidhu786 commited on
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End of training

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Files changed (3) hide show
  1. README.md +26 -26
  2. model.safetensors +1 -1
  3. runs/Aug04_04-45-05_26f492c0f4ad/events.out.tfevents.1722746721.26f492c0f4ad.487.0 +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: 0.83
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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
@@ -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 [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the GTZAN dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8269
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- - Accuracy: 0.83
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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: 5e-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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- | 2.1788 | 1.0 | 57 | 2.0907 | 0.39 |
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- | 1.6561 | 2.0 | 114 | 1.5747 | 0.62 |
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- | 1.3464 | 3.0 | 171 | 1.4279 | 0.57 |
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- | 1.1727 | 4.0 | 228 | 1.1862 | 0.68 |
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- | 0.9399 | 5.0 | 285 | 1.0572 | 0.66 |
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- | 0.931 | 6.0 | 342 | 1.1268 | 0.66 |
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- | 0.7375 | 7.0 | 399 | 0.8744 | 0.77 |
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- | 0.5798 | 8.0 | 456 | 0.8596 | 0.78 |
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- | 0.5668 | 9.0 | 513 | 0.8253 | 0.76 |
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- | 0.4972 | 10.0 | 570 | 0.8273 | 0.76 |
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- | 0.2375 | 11.0 | 627 | 0.8192 | 0.76 |
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- | 0.1913 | 12.0 | 684 | 0.7618 | 0.83 |
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- | 0.2132 | 13.0 | 741 | 0.8249 | 0.82 |
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- | 0.0823 | 14.0 | 798 | 0.8962 | 0.81 |
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- | 0.0444 | 15.0 | 855 | 0.9376 | 0.78 |
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- | 0.0375 | 16.0 | 912 | 0.8609 | 0.81 |
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- | 0.0298 | 17.0 | 969 | 0.8741 | 0.83 |
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- | 0.0808 | 18.0 | 1026 | 0.8911 | 0.84 |
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- | 0.0453 | 19.0 | 1083 | 0.8756 | 0.84 |
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- | 0.0229 | 20.0 | 1140 | 0.8269 | 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: 0.88
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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 [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the GTZAN dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6028
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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: 3e-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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+ | 2.0751 | 1.0 | 113 | 2.0343 | 0.6 |
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+ | 1.5734 | 2.0 | 226 | 1.6338 | 0.58 |
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+ | 1.3801 | 3.0 | 339 | 1.2674 | 0.7 |
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+ | 1.0384 | 4.0 | 452 | 1.1376 | 0.68 |
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+ | 0.973 | 5.0 | 565 | 0.9849 | 0.73 |
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+ | 1.0033 | 6.0 | 678 | 0.7686 | 0.76 |
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+ | 0.6347 | 7.0 | 791 | 0.5909 | 0.87 |
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+ | 0.6537 | 8.0 | 904 | 0.9489 | 0.75 |
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+ | 0.359 | 9.0 | 1017 | 0.7478 | 0.81 |
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+ | 0.2268 | 10.0 | 1130 | 0.6247 | 0.84 |
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+ | 0.2674 | 11.0 | 1243 | 0.6437 | 0.84 |
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+ | 0.2237 | 12.0 | 1356 | 0.7997 | 0.81 |
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+ | 0.1418 | 13.0 | 1469 | 0.7738 | 0.84 |
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+ | 0.1201 | 14.0 | 1582 | 0.5696 | 0.87 |
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+ | 0.019 | 15.0 | 1695 | 0.8173 | 0.84 |
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+ | 0.0175 | 16.0 | 1808 | 0.6395 | 0.88 |
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+ | 0.16 | 17.0 | 1921 | 0.6062 | 0.87 |
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+ | 0.0137 | 18.0 | 2034 | 0.5422 | 0.9 |
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+ | 0.0127 | 19.0 | 2147 | 0.6421 | 0.88 |
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+ | 0.0129 | 20.0 | 2260 | 0.6028 | 0.88 |
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  ### Framework versions
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