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CodingQueen13
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distilhubert-finetuned-gtzan

Audio Classification
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hubert
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  1. README.md +22 -26
  2. model.safetensors +1 -1
  3. runs/Sep09_09-51-15_c3f9c4d4f413/events.out.tfevents.1725875477.c3f9c4d4f413.533.0 +2 -2
README.md CHANGED
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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:
@@ -22,7 +23,7 @@ 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 +33,8 @@ 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: 0.8931
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- - Accuracy: 0.84
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  ## Model description
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@@ -58,39 +59,34 @@ The following hyperparameters were used during training:
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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: cosine
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- - lr_scheduler_warmup_ratio: 0.05
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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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- | 1.9292 | 1.0 | 113 | 1.8783 | 0.49 |
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- | 1.1771 | 2.0 | 226 | 1.2910 | 0.64 |
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- | 0.9343 | 3.0 | 339 | 1.0554 | 0.67 |
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- | 0.5929 | 4.0 | 452 | 0.8423 | 0.75 |
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- | 0.5678 | 5.0 | 565 | 0.7333 | 0.78 |
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- | 0.2351 | 6.0 | 678 | 0.6266 | 0.84 |
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- | 0.2348 | 7.0 | 791 | 0.6047 | 0.81 |
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- | 0.0834 | 8.0 | 904 | 0.7525 | 0.82 |
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- | 0.0374 | 9.0 | 1017 | 0.8083 | 0.82 |
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- | 0.0089 | 10.0 | 1130 | 0.7745 | 0.83 |
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- | 0.0068 | 11.0 | 1243 | 0.7883 | 0.85 |
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- | 0.0046 | 12.0 | 1356 | 0.8266 | 0.84 |
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- | 0.004 | 13.0 | 1469 | 0.8557 | 0.84 |
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- | 0.0038 | 14.0 | 1582 | 0.9485 | 0.83 |
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- | 0.0031 | 15.0 | 1695 | 0.9042 | 0.84 |
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- | 0.0031 | 16.0 | 1808 | 0.8945 | 0.84 |
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- | 0.0031 | 17.0 | 1921 | 0.8780 | 0.84 |
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- | 0.0026 | 18.0 | 2034 | 0.9071 | 0.84 |
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- | 0.0027 | 19.0 | 2147 | 0.8932 | 0.84 |
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- | 0.0027 | 20.0 | 2260 | 0.8931 | 0.84 |
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  ### Framework versions
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- - Transformers 4.42.4
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  - Pytorch 2.4.0+cu121
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  - Datasets 2.21.0
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  - Tokenizers 0.19.1
 
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  ---
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+ library_name: transformers
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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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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.82
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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: 0.6191
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+ - Accuracy: 0.82
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  ## Model description
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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: cosine
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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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+ | 2.1554 | 1.0 | 113 | 2.0427 | 0.44 |
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+ | 1.5528 | 2.0 | 226 | 1.5599 | 0.5 |
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+ | 1.3212 | 3.0 | 339 | 1.1755 | 0.6 |
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+ | 0.9075 | 4.0 | 452 | 0.9560 | 0.73 |
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+ | 0.7823 | 5.0 | 565 | 0.8967 | 0.74 |
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+ | 0.7262 | 6.0 | 678 | 0.6578 | 0.8 |
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+ | 0.5761 | 7.0 | 791 | 0.6274 | 0.81 |
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+ | 0.3797 | 8.0 | 904 | 0.6923 | 0.82 |
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+ | 0.4168 | 9.0 | 1017 | 0.5700 | 0.84 |
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+ | 0.2646 | 10.0 | 1130 | 0.6484 | 0.81 |
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+ | 0.1952 | 11.0 | 1243 | 0.5925 | 0.84 |
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+ | 0.1403 | 12.0 | 1356 | 0.6551 | 0.82 |
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+ | 0.1558 | 13.0 | 1469 | 0.6271 | 0.82 |
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+ | 0.4606 | 14.0 | 1582 | 0.6272 | 0.82 |
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+ | 0.2095 | 15.0 | 1695 | 0.6191 | 0.82 |
 
 
 
 
 
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  ### Framework versions
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+ - Transformers 4.44.2
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  - Pytorch 2.4.0+cu121
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  - Datasets 2.21.0
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  - Tokenizers 0.19.1
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