readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - audiofolder
  model-index:
  - name: wav2vec2-large-xls-r-300m-medical
    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-large-xls-r-300m-medical
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the audiofolder dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2214
  - Wer: 0.0975
  
  ## 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: 0.0003
  - train_batch_size: 16
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 50
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 7.0393        | 2.47  | 200  | 3.2401          | 1.0    |
  | 2.8825        | 4.94  | 400  | 1.0054          | 0.8592 |
  | 0.4256        | 7.41  | 600  | 0.2495          | 0.2448 |
  | 0.1585        | 9.88  | 800  | 0.2169          | 0.1816 |
  | 0.1017        | 12.35 | 1000 | 0.2197          | 0.1615 |
  | 0.0728        | 14.81 | 1200 | 0.2018          | 0.1582 |
  | 0.0608        | 17.28 | 1400 | 0.2108          | 0.1462 |
  | 0.0485        | 19.75 | 1600 | 0.2169          | 0.1301 |
  | 0.0391        | 22.22 | 1800 | 0.2180          | 0.1381 |
  | 0.0349        | 24.69 | 2000 | 0.2166          | 0.1241 |
  | 0.0314        | 27.16 | 2200 | 0.2124          | 0.1189 |
  | 0.0268        | 29.63 | 2400 | 0.2087          | 0.1185 |
  | 0.0243        | 32.1  | 2600 | 0.2133          | 0.1112 |
  | 0.021         | 34.57 | 2800 | 0.2199          | 0.1153 |
  | 0.02          | 37.04 | 3000 | 0.2147          | 0.1134 |
  | 0.017         | 39.51 | 3200 | 0.2205          | 0.1037 |
  | 0.0152        | 41.98 | 3400 | 0.2174          | 0.1039 |
  | 0.0137        | 44.44 | 3600 | 0.2215          | 0.0988 |
  | 0.0124        | 46.91 | 3800 | 0.2234          | 0.1003 |
  | 0.0112        | 49.38 | 4000 | 0.2214          | 0.0975 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  