readme: ---
  license: apache-2.0
  tags:
  - hf-course
  - generated_from_trainer
  datasets:
  - marsyas/gtzan
  metrics:
  - accuracy
  model-index:
  - name: distilhubert-finetuned-gtzan
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # distilhubert-finetuned-gtzan
  
  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6694
  - Accuracy: 0.82
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 5e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 0.99  | 56   | 1.9426          | 0.5      |
  | No log        | 1.99  | 112  | 1.4157          | 0.63     |
  | No log        | 2.99  | 168  | 1.1351          | 0.69     |
  | No log        | 3.99  | 224  | 1.0285          | 0.72     |
  | No log        | 4.99  | 280  | 0.8538          | 0.79     |
  | No log        | 5.99  | 336  | 0.8015          | 0.74     |
  | No log        | 6.99  | 392  | 0.6694          | 0.82     |
  | No log        | 7.99  | 448  | 0.6779          | 0.79     |
  | 1.0811        | 8.99  | 504  | 0.6414          | 0.81     |
  | 1.0811        | 9.99  | 560  | 0.6443          | 0.82     |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.11.0
  - Datasets 2.6.1
  - Tokenizers 0.11.6
  