readme: ---
  license: bsd-3-clause
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: ast-finetuned-audioset-10-10-0.4593-finetuning-ESC-50-slower-LR
    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. -->
  
  # ast-finetuned-audioset-10-10-0.4593-finetuning-ESC-50-slower-LR
  
  This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7837
  - Accuracy: 0.8929
  
  ## 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: 3e-06
  - train_batch_size: 2
  - eval_batch_size: 2
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 8
  - 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
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 9.3646        | 1.0   | 28   | 6.0136          | 0.0893   |
  | 2.9631        | 2.0   | 56   | 2.0175          | 0.5357   |
  | 1.2435        | 3.0   | 84   | 1.1471          | 0.7679   |
  | 0.7699        | 4.0   | 112  | 0.8559          | 0.875    |
  | 0.5911        | 5.0   | 140  | 0.7837          | 0.8929   |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  