readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-demo-F01-2
    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-F01-2
  
  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: 1.6361
  - Wer: 0.9025
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 23.7408       | 0.81  | 500   | 3.3782          | 1.0    |
  | 3.348         | 1.62  | 1000  | 2.9501          | 1.0    |
  | 2.8539        | 2.44  | 1500  | 2.6975          | 1.0    |
  | 2.311         | 3.25  | 2000  | 1.7770          | 1.3175 |
  | 1.5102        | 4.06  | 2500  | 1.3481          | 1.3515 |
  | 1.0616        | 4.87  | 3000  | 1.4306          | 1.2313 |
  | 0.8493        | 5.68  | 3500  | 1.2261          | 1.1701 |
  | 0.7058        | 6.49  | 4000  | 1.2132          | 1.1111 |
  | 0.6129        | 7.31  | 4500  | 1.4230          | 1.1429 |
  | 0.5513        | 8.12  | 5000  | 1.2003          | 1.0499 |
  | 0.4957        | 8.93  | 5500  | 1.5534          | 1.1043 |
  | 0.4456        | 9.74  | 6000  | 1.2315          | 1.0658 |
  | 0.4101        | 10.55 | 6500  | 1.1621          | 1.0680 |
  | 0.3776        | 11.36 | 7000  | 1.4302          | 1.0385 |
  | 0.3318        | 12.18 | 7500  | 1.3488          | 0.9977 |
  | 0.3189        | 12.99 | 8000  | 1.4050          | 1.0295 |
  | 0.3103        | 13.8  | 8500  | 1.4535          | 1.0385 |
  | 0.2791        | 14.61 | 9000  | 1.3318          | 1.0181 |
  | 0.2681        | 15.42 | 9500  | 1.5199          | 0.9909 |
  | 0.2352        | 16.23 | 10000 | 1.5019          | 1.0023 |
  | 0.235         | 17.05 | 10500 | 1.7984          | 0.9955 |
  | 0.2319        | 17.86 | 11000 | 1.3399          | 0.9705 |
  | 0.221         | 18.67 | 11500 | 1.8316          | 0.9342 |
  | 0.2154        | 19.48 | 12000 | 1.6837          | 0.9637 |
  | 0.1911        | 20.29 | 12500 | 1.6999          | 0.9388 |
  | 0.1754        | 21.1  | 13000 | 1.4801          | 0.9274 |
  | 0.1776        | 21.92 | 13500 | 1.7954          | 0.9206 |
  | 0.1616        | 22.73 | 14000 | 1.7891          | 0.9320 |
  | 0.1579        | 23.54 | 14500 | 1.5692          | 0.9116 |
  | 0.173         | 24.35 | 15000 | 1.4928          | 0.9048 |
  | 0.1561        | 25.16 | 15500 | 1.6492          | 0.9116 |
  | 0.1542        | 25.97 | 16000 | 1.7356          | 0.9048 |
  | 0.131         | 26.79 | 16500 | 1.7785          | 0.9048 |
  | 0.1295        | 27.6  | 17000 | 1.6532          | 0.9116 |
  | 0.1374        | 28.41 | 17500 | 1.6760          | 0.9093 |
  | 0.1186        | 29.22 | 18000 | 1.6361          | 0.9025 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 1.18.3
  - Tokenizers 0.13.2
  