readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: distilhubert-finetuned-music-genres-small
    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-music-genres-small
  
  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.6827
  - Accuracy: 0.4
  
  ## 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: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | No log        | 0.99  | 56   | 2.0784          | 0.36     |
  | 2.098         | 1.99  | 112  | 1.8533          | 0.35     |
  | 2.098         | 2.99  | 168  | 1.7524          | 0.39     |
  | 1.7241        | 3.99  | 224  | 1.6827          | 0.4      |
  | 1.7241        | 4.99  | 280  | 1.6565          | 0.39     |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.11.0
  - Datasets 2.6.1
  - Tokenizers 0.11.6
  