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pranjalks
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distilhubert-finetuned-gtzan

Audio Classification
Transformers
PyTorch
hubert
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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  1. README.md +19 -19
  2. pytorch_model.bin +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: 0.85
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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: 0.9537
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- - Accuracy: 0.85
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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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- | 2.1442 | 1.0 | 113 | 2.0322 | 0.37 |
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- | 1.4292 | 2.0 | 226 | 1.4054 | 0.61 |
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- | 1.0171 | 3.0 | 339 | 1.0432 | 0.72 |
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- | 1.131 | 4.0 | 452 | 0.9372 | 0.69 |
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- | 0.6039 | 5.0 | 565 | 0.7687 | 0.76 |
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- | 0.3424 | 6.0 | 678 | 0.6952 | 0.81 |
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- | 0.4153 | 7.0 | 791 | 0.6242 | 0.82 |
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- | 0.0684 | 8.0 | 904 | 0.7415 | 0.83 |
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- | 0.173 | 9.0 | 1017 | 0.7256 | 0.84 |
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- | 0.0182 | 10.0 | 1130 | 0.8752 | 0.83 |
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- | 0.0127 | 11.0 | 1243 | 0.8816 | 0.83 |
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- | 0.1058 | 12.0 | 1356 | 0.9401 | 0.85 |
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- | 0.0073 | 13.0 | 1469 | 0.9321 | 0.86 |
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- | 0.0081 | 14.0 | 1582 | 0.9589 | 0.85 |
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- | 0.0069 | 15.0 | 1695 | 0.9537 | 0.85 |
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  ### Framework versions
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- - Transformers 4.32.0.dev0
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.14.4
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  - Tokenizers 0.13.3
 
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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
 
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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: 0.8438
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+ - Accuracy: 0.84
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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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+ | 2.1199 | 1.0 | 113 | 2.0015 | 0.48 |
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+ | 1.4342 | 2.0 | 226 | 1.3339 | 0.62 |
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+ | 1.1096 | 3.0 | 339 | 1.0138 | 0.72 |
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+ | 1.0446 | 4.0 | 452 | 0.8484 | 0.74 |
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+ | 0.6716 | 5.0 | 565 | 0.7406 | 0.75 |
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+ | 0.3906 | 6.0 | 678 | 0.6848 | 0.81 |
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+ | 0.335 | 7.0 | 791 | 0.5893 | 0.81 |
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+ | 0.141 | 8.0 | 904 | 0.7190 | 0.79 |
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+ | 0.1962 | 9.0 | 1017 | 0.7019 | 0.84 |
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+ | 0.0604 | 10.0 | 1130 | 0.7604 | 0.83 |
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+ | 0.0141 | 11.0 | 1243 | 0.8239 | 0.83 |
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+ | 0.0982 | 12.0 | 1356 | 0.7948 | 0.84 |
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+ | 0.0086 | 13.0 | 1469 | 0.8192 | 0.84 |
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+ | 0.0078 | 14.0 | 1582 | 0.8407 | 0.83 |
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+ | 0.0073 | 15.0 | 1695 | 0.8438 | 0.84 |
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  ### Framework versions
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+ - Transformers 4.33.0.dev0
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  - Pytorch 2.0.1+cu118
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  - Datasets 2.14.4
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  - Tokenizers 0.13.3
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