readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-demo-M01-2
    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-M01-2
  
  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: 1.8002
  - Wer: 0.9717
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 23.0778       | 0.9   | 500   | 3.3183          | 1.0    |
  | 3.3341        | 1.8   | 1000  | 3.1046          | 1.0    |
  | 2.8465        | 2.7   | 1500  | 2.7012          | 1.0    |
  | 2.4301        | 3.6   | 2000  | 1.9785          | 1.3025 |
  | 1.5285        | 4.5   | 2500  | 1.5775          | 1.4170 |
  | 1.055         | 5.41  | 3000  | 1.5070          | 1.3753 |
  | 0.8075        | 6.31  | 3500  | 1.3811          | 1.2509 |
  | 0.6867        | 7.21  | 4000  | 1.2362          | 1.2007 |
  | 0.566         | 8.11  | 4500  | 1.6537          | 1.2064 |
  | 0.4967        | 9.01  | 5000  | 1.5271          | 1.1562 |
  | 0.4337        | 9.91  | 5500  | 1.2359          | 1.1046 |
  | 0.3941        | 10.81 | 6000  | 1.5255          | 1.1237 |
  | 0.3612        | 11.71 | 6500  | 1.3686          | 1.0890 |
  | 0.3237        | 12.61 | 7000  | 1.1992          | 1.0629 |
  | 0.3085        | 13.51 | 7500  | 1.5883          | 1.0834 |
  | 0.3003        | 14.41 | 8000  | 1.7352          | 1.0686 |
  | 0.2859        | 15.32 | 8500  | 1.4790          | 0.9958 |
  | 0.2495        | 16.22 | 9000  | 1.6757          | 1.0155 |
  | 0.2329        | 17.12 | 9500  | 1.5789          | 1.0283 |
  | 0.2241        | 18.02 | 10000 | 1.5147          | 0.9922 |
  | 0.215         | 18.92 | 10500 | 1.4684          | 0.9965 |
  | 0.202         | 19.82 | 11000 | 1.5099          | 0.9760 |
  | 0.1942        | 20.72 | 11500 | 1.8195          | 0.9837 |
  | 0.1627        | 21.62 | 12000 | 1.8089          | 1.0021 |
  | 0.1782        | 22.52 | 12500 | 1.6944          | 0.9710 |
  | 0.1566        | 23.42 | 13000 | 1.5881          | 0.9682 |
  | 0.1471        | 24.32 | 13500 | 1.6741          | 0.9654 |
  | 0.1355        | 25.23 | 14000 | 1.6183          | 0.9576 |
  | 0.1253        | 26.13 | 14500 | 1.5730          | 0.9696 |
  | 0.1245        | 27.03 | 15000 | 1.6876          | 0.9689 |
  | 0.1258        | 27.93 | 15500 | 1.7535          | 0.9802 |
  | 0.1217        | 28.83 | 16000 | 1.7710          | 0.9661 |
  | 0.1074        | 29.73 | 16500 | 1.8002          | 0.9717 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 1.18.3
  - Tokenizers 0.13.2
  