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pmano2
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distilhubert-finetuned-gtzan

Audio Classification
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hubert
Generated from Trainer
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Files changed (3) hide show
  1. README.md +14 -14
  2. model.safetensors +1 -1
  3. runs/Jan20_01-03-16_0474458f40c0/events.out.tfevents.1705712612.0474458f40c0.12351.0 +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 [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: 0.6399
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- - Accuracy: 0.83
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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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- | 2.0149 | 1.0 | 113 | 1.8312 | 0.45 |
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- | 1.3438 | 2.0 | 226 | 1.1735 | 0.63 |
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- | 1.0285 | 3.0 | 339 | 0.9119 | 0.73 |
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- | 0.8525 | 4.0 | 452 | 0.8857 | 0.74 |
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- | 0.5617 | 5.0 | 565 | 0.7207 | 0.76 |
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- | 0.3951 | 6.0 | 678 | 0.7255 | 0.79 |
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- | 0.3874 | 7.0 | 791 | 0.5954 | 0.82 |
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- | 0.1297 | 8.0 | 904 | 0.6241 | 0.82 |
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- | 0.1832 | 9.0 | 1017 | 0.5982 | 0.86 |
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- | 0.0734 | 10.0 | 1130 | 0.6399 | 0.83 |
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  ### Framework versions
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- - Transformers 4.37.0.dev0
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  - Pytorch 2.1.0+cu121
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  - Datasets 2.16.1
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  - Tokenizers 0.15.0
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.79
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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: 0.6904
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+ - Accuracy: 0.79
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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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+ | 2.0975 | 1.0 | 113 | 1.8922 | 0.52 |
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+ | 1.5102 | 2.0 | 226 | 1.2591 | 0.65 |
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+ | 1.1763 | 3.0 | 339 | 0.9755 | 0.72 |
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+ | 0.9729 | 4.0 | 452 | 0.8941 | 0.75 |
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+ | 0.7546 | 5.0 | 565 | 0.7343 | 0.78 |
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+ | 0.5046 | 6.0 | 678 | 0.7324 | 0.78 |
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+ | 0.6277 | 7.0 | 791 | 0.6579 | 0.8 |
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+ | 0.3472 | 8.0 | 904 | 0.6160 | 0.81 |
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+ | 0.5776 | 9.0 | 1017 | 0.7029 | 0.78 |
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+ | 0.3091 | 10.0 | 1130 | 0.6904 | 0.79 |
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  ### Framework versions
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+ - Transformers 4.38.0.dev0
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  - Pytorch 2.1.0+cu121
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  - Datasets 2.16.1
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  - Tokenizers 0.15.0
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