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End of training

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  1. README.md +15 -15
  2. model.safetensors +1 -1
README.md CHANGED
@@ -8,7 +8,7 @@ datasets:
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  metrics:
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  - accuracy
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  model-index:
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- - name: distilhubert-finetuned-gtzan
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  results:
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  - task:
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  name: Audio Classification
@@ -22,18 +22,18 @@ 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
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  should probably proofread and complete it, then remove this comment. -->
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- # distilhubert-finetuned-gtzan
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  This model is a fine-tuned version of [gnuevo/distilhubert-finetuned-gtzan](https://huggingface.co/gnuevo/distilhubert-finetuned-gtzan) on the GTZAN dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6408
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- - Accuracy: 0.83
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  ## Model description
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@@ -66,16 +66,16 @@ 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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- | 2.2638 | 1.0 | 57 | 2.2585 | 0.17 |
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- | 1.9343 | 2.0 | 114 | 1.9475 | 0.6 |
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- | 1.2679 | 3.0 | 171 | 1.4426 | 0.7 |
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- | 0.6692 | 4.0 | 228 | 1.0634 | 0.74 |
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- | 0.4132 | 5.0 | 285 | 0.8203 | 0.82 |
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- | 0.188 | 6.0 | 342 | 0.6990 | 0.85 |
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- | 0.1295 | 7.0 | 399 | 0.6518 | 0.83 |
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- | 0.2153 | 8.0 | 456 | 0.6430 | 0.84 |
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- | 0.1812 | 9.0 | 513 | 0.6403 | 0.83 |
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- | 0.3722 | 10.0 | 570 | 0.6408 | 0.83 |
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  ### Framework versions
 
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  metrics:
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  - accuracy
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  model-index:
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+ - name: distilhubert-finetuned-gtzan-finetuned-gtzan
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  results:
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  - task:
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  name: Audio Classification
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.86
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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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  should probably proofread and complete it, then remove this comment. -->
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+ # distilhubert-finetuned-gtzan-finetuned-gtzan
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  This model is a fine-tuned version of [gnuevo/distilhubert-finetuned-gtzan](https://huggingface.co/gnuevo/distilhubert-finetuned-gtzan) on the GTZAN dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6268
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+ - Accuracy: 0.86
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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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+ | 2.2951 | 1.0 | 57 | 2.3060 | 0.09 |
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+ | 2.1105 | 2.0 | 114 | 2.1233 | 0.57 |
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+ | 1.4664 | 3.0 | 171 | 1.5734 | 0.61 |
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+ | 0.8475 | 4.0 | 228 | 1.1321 | 0.66 |
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+ | 0.467 | 5.0 | 285 | 0.8660 | 0.73 |
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+ | 0.2699 | 6.0 | 342 | 0.7317 | 0.84 |
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+ | 0.1908 | 7.0 | 399 | 0.6568 | 0.86 |
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+ | 0.2298 | 8.0 | 456 | 0.6328 | 0.86 |
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+ | 0.2495 | 9.0 | 513 | 0.6270 | 0.86 |
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+ | 0.3529 | 10.0 | 570 | 0.6268 | 0.86 |
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  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
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