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distilhubert-finetuned-gtzan

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hubert
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update model card README.md

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  1. README.md +10 -15
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@@ -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: 0.86
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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
@@ -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: 0.8060
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- - Accuracy: 0.86
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  ## Model description
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@@ -52,29 +52,24 @@ 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: 1e-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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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 10
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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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- | 1.4315 | 1.0 | 7 | 0.5652 | 0.94 |
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- | 1.8803 | 2.0 | 14 | 0.5438 | 0.9 |
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- | 1.236 | 3.0 | 21 | 0.5891 | 0.9 |
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- | 0.6882 | 4.0 | 28 | 0.6378 | 0.9 |
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- | 0.6126 | 5.0 | 35 | 0.6965 | 0.88 |
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- | 0.6847 | 6.0 | 42 | 0.7258 | 0.84 |
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- | 0.3871 | 7.0 | 49 | 0.7459 | 0.84 |
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- | 0.2981 | 8.0 | 56 | 0.8024 | 0.86 |
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- | 0.1321 | 9.0 | 63 | 0.8140 | 0.86 |
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- | 0.2443 | 10.0 | 70 | 0.8060 | 0.86 |
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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 [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: 0.7321
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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: 2e-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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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 5
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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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+ | 1.0326 | 1.0 | 7 | 0.5762 | 0.9 |
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+ | 0.95 | 2.0 | 14 | 0.5924 | 0.9 |
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+ | 0.9304 | 3.0 | 21 | 0.5446 | 0.9 |
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+ | 0.4207 | 4.0 | 28 | 0.6466 | 0.88 |
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+ | 0.261 | 5.0 | 35 | 0.7321 | 0.88 |
 
 
 
 
 
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  ### Framework versions