readme: ---
  license: apache-2.0
  tags:
  - audio-classification
  - generated_from_trainer
  datasets:
  - mir_st500
  metrics:
  - accuracy
  model-index:
  - name: wav2vec2-base-mirst500
    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. -->
  
  # wav2vec2-base-mirst500
  
  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the /workspace/datasets/datasets/MIR_ST500/MIR_ST500_AUDIO_CLASSIFICATION.py dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8678
  - Accuracy: 0.7017
  
  ## 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-05
  - train_batch_size: 16
  - eval_batch_size: 1
  - seed: 0
  - distributed_type: multi-GPU
  - num_devices: 2
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 128
  - total_eval_batch_size: 2
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 5.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 1.1999        | 1.0   | 1304 | 1.1029          | 0.5877   |
  | 1.0779        | 2.0   | 2608 | 0.9455          | 0.6555   |
  | 0.9775        | 3.0   | 3912 | 0.9670          | 0.6523   |
  | 0.9542        | 4.0   | 5216 | 0.8810          | 0.6946   |
  | 0.9403        | 5.0   | 6520 | 0.8678          | 0.7017   |
  
  
  ### Framework versions
  
  - Transformers 4.15.0
  - Pytorch 1.9.1+cu102
  - Datasets 2.0.0
  - Tokenizers 0.10.3
  