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distilhubert-finetuned-gtzan-finetuned-gtzan

Audio Classification
Transformers
PyTorch
hubert
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
benjipeng commited on
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End of training

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  1. README.md +12 -9
  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: 0.84
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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
@@ -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 [benjipeng/distilhubert-finetuned-gtzan](https://huggingface.co/benjipeng/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: 0.8958
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- - Accuracy: 0.84
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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: 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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- | 0.121 | 1.0 | 113 | 0.7727 | 0.79 |
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- | 0.2343 | 2.0 | 226 | 0.8966 | 0.8 |
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- | 0.1278 | 3.0 | 339 | 0.8448 | 0.86 |
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- | 0.0054 | 4.0 | 452 | 0.9292 | 0.84 |
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- | 0.0047 | 5.0 | 565 | 0.8958 | 0.84 |
 
 
 
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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: 0.86
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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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  This model is a fine-tuned version of [benjipeng/distilhubert-finetuned-gtzan](https://huggingface.co/benjipeng/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: 0.6143
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+ - Accuracy: 0.86
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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: 8
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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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+ | 0.8153 | 1.0 | 113 | 0.7412 | 0.8 |
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+ | 0.6209 | 2.0 | 226 | 0.8662 | 0.75 |
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+ | 0.3642 | 3.0 | 339 | 0.5880 | 0.84 |
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+ | 0.2077 | 4.0 | 452 | 0.6017 | 0.85 |
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+ | 0.1658 | 5.0 | 565 | 0.5087 | 0.87 |
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+ | 0.0209 | 6.0 | 678 | 0.6488 | 0.85 |
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+ | 0.1971 | 7.0 | 791 | 0.5813 | 0.87 |
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+ | 0.0047 | 8.0 | 904 | 0.6143 | 0.86 |
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  ### Framework versions
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