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Aryan-401
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distilhubert-finetuned-gtzan

Audio Classification
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hubert
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  1. README.md +20 -15
  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: 0.83
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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: 0.5144
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- - Accuracy: 0.83
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  ## Model description
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@@ -59,28 +59,33 @@ The following hyperparameters were used during training:
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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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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 10
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 1.9989 | 1.0 | 113 | 1.8815 | 0.48 |
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- | 1.2023 | 2.0 | 226 | 1.2623 | 0.59 |
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- | 0.9464 | 3.0 | 339 | 0.9253 | 0.77 |
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- | 0.7043 | 4.0 | 452 | 0.7634 | 0.76 |
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- | 0.4678 | 5.0 | 565 | 0.6706 | 0.79 |
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- | 0.4217 | 6.0 | 678 | 0.6455 | 0.8 |
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- | 0.3151 | 7.0 | 791 | 0.6370 | 0.81 |
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- | 0.203 | 8.0 | 904 | 0.5110 | 0.84 |
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- | 0.1422 | 9.0 | 1017 | 0.5265 | 0.83 |
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- | 0.1084 | 10.0 | 1130 | 0.5144 | 0.83 |
 
 
 
 
 
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  ### Framework versions
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  - Transformers 4.35.2
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  - Pytorch 2.1.0+cu121
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- - Datasets 2.15.0
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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: 0.85
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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
 
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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: 0.7207
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+ - Accuracy: 0.85
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  ## Model description
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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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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 15
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 2.0917 | 1.0 | 113 | 1.9773 | 0.48 |
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+ | 1.3655 | 2.0 | 226 | 1.3419 | 0.62 |
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+ | 0.9901 | 3.0 | 339 | 0.9640 | 0.75 |
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+ | 0.8565 | 4.0 | 452 | 0.7732 | 0.81 |
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+ | 0.6259 | 5.0 | 565 | 0.7502 | 0.8 |
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+ | 0.4507 | 6.0 | 678 | 0.6888 | 0.81 |
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+ | 0.4018 | 7.0 | 791 | 0.7404 | 0.8 |
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+ | 0.1275 | 8.0 | 904 | 0.6718 | 0.83 |
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+ | 0.1077 | 9.0 | 1017 | 0.6175 | 0.86 |
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+ | 0.028 | 10.0 | 1130 | 0.6317 | 0.86 |
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+ | 0.0867 | 11.0 | 1243 | 0.6053 | 0.88 |
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+ | 0.0149 | 12.0 | 1356 | 0.7164 | 0.85 |
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+ | 0.0108 | 13.0 | 1469 | 0.7224 | 0.85 |
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+ | 0.0101 | 14.0 | 1582 | 0.7101 | 0.84 |
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+ | 0.0096 | 15.0 | 1695 | 0.7207 | 0.85 |
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  ### Framework versions
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  - Transformers 4.35.2
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  - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.0
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  - Tokenizers 0.15.0
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