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HamzaSidhu786
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distilhubert-finetuned-gtzan

Audio Classification
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wav2vec2
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  1. README.md +32 -27
  2. model.safetensors +1 -1
  3. runs/Aug03_20-36-27_c3c751c6bd7c/events.out.tfevents.1722717439.c3c751c6bd7c.231.0 +2 -2
README.md CHANGED
@@ -1,6 +1,6 @@
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  ---
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  license: apache-2.0
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- base_model: ntu-spml/distilhubert
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  tags:
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  - generated_from_trainer
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  datasets:
@@ -8,7 +8,7 @@ datasets:
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  metrics:
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  - accuracy
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  model-index:
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- - name: distilhubert-finetuned-gtzan
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  results:
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  - task:
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  name: Audio Classification
@@ -22,18 +22,18 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.81
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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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  should probably proofread and complete it, then remove this comment. -->
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- # distilhubert-finetuned-gtzan
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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: 0.9459
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- - Accuracy: 0.81
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  ## Model description
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@@ -53,39 +53,44 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-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: 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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- | 2.1346 | 1.0 | 113 | 2.0097 | 0.52 |
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- | 1.3431 | 2.0 | 226 | 1.3485 | 0.63 |
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- | 1.0836 | 3.0 | 339 | 1.0567 | 0.7 |
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- | 0.707 | 4.0 | 452 | 0.9165 | 0.73 |
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- | 0.6421 | 5.0 | 565 | 0.7648 | 0.79 |
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- | 0.4217 | 6.0 | 678 | 0.8743 | 0.76 |
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- | 0.2786 | 7.0 | 791 | 0.7573 | 0.8 |
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- | 0.1399 | 8.0 | 904 | 0.8341 | 0.75 |
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- | 0.0586 | 9.0 | 1017 | 0.8662 | 0.81 |
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- | 0.0246 | 10.0 | 1130 | 0.9017 | 0.8 |
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- | 0.0139 | 11.0 | 1243 | 0.8831 | 0.79 |
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- | 0.0106 | 12.0 | 1356 | 0.9298 | 0.82 |
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- | 0.0092 | 13.0 | 1469 | 0.9264 | 0.81 |
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- | 0.0087 | 14.0 | 1582 | 0.9466 | 0.82 |
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- | 0.0071 | 15.0 | 1695 | 0.9459 | 0.81 |
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.41.2
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- - Pytorch 2.3.0+cu121
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  - Datasets 2.20.0
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  - Tokenizers 0.19.1
 
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  ---
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  license: apache-2.0
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+ base_model: facebook/wav2vec2-base
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  tags:
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  - generated_from_trainer
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  datasets:
 
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  metrics:
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  - accuracy
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  model-index:
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+ - name: HamzaSidhu786/distilhubert-finetuned-gtzan
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  results:
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  - task:
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  name: Audio Classification
 
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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
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  should probably proofread and complete it, then remove this comment. -->
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+ # HamzaSidhu786/distilhubert-finetuned-gtzan
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+ This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the GTZAN dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8269
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+ - Accuracy: 0.83
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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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: 20
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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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+ | 2.1788 | 1.0 | 57 | 2.0907 | 0.39 |
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+ | 1.6561 | 2.0 | 114 | 1.5747 | 0.62 |
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+ | 1.3464 | 3.0 | 171 | 1.4279 | 0.57 |
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+ | 1.1727 | 4.0 | 228 | 1.1862 | 0.68 |
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+ | 0.9399 | 5.0 | 285 | 1.0572 | 0.66 |
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+ | 0.931 | 6.0 | 342 | 1.1268 | 0.66 |
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+ | 0.7375 | 7.0 | 399 | 0.8744 | 0.77 |
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+ | 0.5798 | 8.0 | 456 | 0.8596 | 0.78 |
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+ | 0.5668 | 9.0 | 513 | 0.8253 | 0.76 |
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+ | 0.4972 | 10.0 | 570 | 0.8273 | 0.76 |
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+ | 0.2375 | 11.0 | 627 | 0.8192 | 0.76 |
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+ | 0.1913 | 12.0 | 684 | 0.7618 | 0.83 |
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+ | 0.2132 | 13.0 | 741 | 0.8249 | 0.82 |
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+ | 0.0823 | 14.0 | 798 | 0.8962 | 0.81 |
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+ | 0.0444 | 15.0 | 855 | 0.9376 | 0.78 |
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+ | 0.0375 | 16.0 | 912 | 0.8609 | 0.81 |
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+ | 0.0298 | 17.0 | 969 | 0.8741 | 0.83 |
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+ | 0.0808 | 18.0 | 1026 | 0.8911 | 0.84 |
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+ | 0.0453 | 19.0 | 1083 | 0.8756 | 0.84 |
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+ | 0.0229 | 20.0 | 1140 | 0.8269 | 0.83 |
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  ### Framework versions
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+ - Transformers 4.42.4
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+ - Pytorch 2.3.1+cu121
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  - Datasets 2.20.0
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  - Tokenizers 0.19.1
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