readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-demo-F04-2
    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-demo-F04-2
  
  This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3203
  - Wer: 0.5353
  
  ## 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: 0.0001
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 30
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 23.5576       | 0.89  | 500   | 3.3654          | 1.0    |
  | 3.3953        | 1.79  | 1000  | 3.1729          | 1.0    |
  | 2.9514        | 2.68  | 1500  | 2.8946          | 1.0    |
  | 2.84          | 3.57  | 2000  | 2.8386          | 1.0    |
  | 2.7685        | 4.46  | 2500  | 2.7147          | 1.0    |
  | 2.5059        | 5.36  | 3000  | 2.1341          | 1.1752 |
  | 1.8907        | 6.25  | 3500  | 1.3604          | 1.2403 |
  | 1.3892        | 7.14  | 4000  | 0.8814          | 1.1989 |
  | 1.0754        | 8.04  | 4500  | 0.6416          | 1.0529 |
  | 0.8795        | 8.93  | 5000  | 0.5760          | 0.9641 |
  | 0.7478        | 9.82  | 5500  | 0.4633          | 0.8790 |
  | 0.6107        | 10.71 | 6000  | 0.3921          | 0.8394 |
  | 0.5445        | 11.61 | 6500  | 0.3579          | 0.7987 |
  | 0.4788        | 12.5  | 7000  | 0.3034          | 0.7470 |
  | 0.4435        | 13.39 | 7500  | 0.2989          | 0.7311 |
  | 0.4057        | 14.29 | 8000  | 0.3366          | 0.7092 |
  | 0.3606        | 15.18 | 8500  | 0.2783          | 0.6892 |
  | 0.343         | 16.07 | 9000  | 0.2593          | 0.6612 |
  | 0.3189        | 16.96 | 9500  | 0.2780          | 0.6460 |
  | 0.277         | 17.86 | 10000 | 0.3266          | 0.6277 |
  | 0.2789        | 18.75 | 10500 | 0.3582          | 0.6253 |
  | 0.2552        | 19.64 | 11000 | 0.3422          | 0.6156 |
  | 0.2416        | 20.54 | 11500 | 0.3387          | 0.6016 |
  | 0.2187        | 21.43 | 12000 | 0.3657          | 0.5845 |
  | 0.2317        | 22.32 | 12500 | 0.2932          | 0.5845 |
  | 0.2091        | 23.21 | 13000 | 0.2551          | 0.5614 |
  | 0.199         | 24.11 | 13500 | 0.3113          | 0.5474 |
  | 0.1777        | 25.0  | 14000 | 0.2895          | 0.5572 |
  | 0.1823        | 25.89 | 14500 | 0.3127          | 0.5456 |
  | 0.179         | 26.79 | 15000 | 0.2945          | 0.5438 |
  | 0.1596        | 27.68 | 15500 | 0.3052          | 0.5322 |
  | 0.1671        | 28.57 | 16000 | 0.3119          | 0.5365 |
  | 0.1564        | 29.46 | 16500 | 0.3203          | 0.5353 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 1.18.3
  - Tokenizers 0.13.2
  