readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: wav2vec2-base-960h-finetuned
    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-960h-finetuned
  
  This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.1430
  - Accuracy: 0.6516
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 128
  - 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
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 2.5958        | 1.0   | 203  | 2.4754          | 0.2714   |
  | 2.0809        | 2.0   | 406  | 1.9972          | 0.3930   |
  | 1.8486        | 3.0   | 609  | 1.6918          | 0.4658   |
  | 1.5857        | 4.0   | 812  | 1.5089          | 0.5186   |
  | 1.4819        | 5.0   | 1015 | 1.4027          | 0.5508   |
  | 1.3859        | 6.0   | 1218 | 1.3146          | 0.5867   |
  | 1.3448        | 7.0   | 1421 | 1.2078          | 0.6281   |
  | 1.2551        | 8.0   | 1624 | 1.1600          | 0.6447   |
  | 1.1506        | 9.0   | 1827 | 1.1595          | 0.6512   |
  | 1.2435        | 10.0  | 2030 | 1.1430          | 0.6516   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  