readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-demo-F04
    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
  
  This model is a fine-tuned version of [yip-i/uaspeech-pretrained](https://huggingface.co/yip-i/uaspeech-pretrained) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 4.4557
  - Wer: 1.0985
  
  ## 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: 1e-05
  - 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 16.8788       | 0.89  | 500   | 3.6172          | 1.0    |
  | 3.0484        | 1.79  | 1000  | 3.3653          | 1.0    |
  | 3.0178        | 2.68  | 1500  | 3.3402          | 1.0    |
  | 3.182         | 3.57  | 2000  | 3.1676          | 1.0103 |
  | 3.0374        | 4.46  | 2500  | 3.5767          | 1.2914 |
  | 2.8118        | 5.36  | 3000  | 3.1389          | 1.0444 |
  | 2.8424        | 6.25  | 3500  | 3.1171          | 1.1454 |
  | 2.8194        | 7.14  | 4000  | 3.1267          | 1.2464 |
  | 2.8052        | 8.04  | 4500  | 3.2637          | 1.0918 |
  | 2.7835        | 8.93  | 5000  | 3.3412          | 1.1052 |
  | 2.7794        | 9.82  | 5500  | 3.4910          | 1.2220 |
  | 2.7405        | 10.71 | 6000  | 3.1507          | 1.2451 |
  | 2.7518        | 11.61 | 6500  | 3.5342          | 1.1618 |
  | 2.7461        | 12.5  | 7000  | 3.7598          | 1.2768 |
  | 2.7315        | 13.39 | 7500  | 3.7623          | 1.2220 |
  | 2.7203        | 14.29 | 8000  | 4.1022          | 1.0730 |
  | 2.6901        | 15.18 | 8500  | 3.6616          | 1.2914 |
  | 2.7152        | 16.07 | 9000  | 3.7305          | 1.2488 |
  | 2.7036        | 16.96 | 9500  | 3.6997          | 1.1454 |
  | 2.6938        | 17.86 | 10000 | 4.9800          | 1.0365 |
  | 2.6962        | 18.75 | 10500 | 4.3985          | 1.1813 |
  | 2.6801        | 19.64 | 11000 | 5.2335          | 1.1910 |
  | 2.6695        | 20.54 | 11500 | 4.4297          | 1.0432 |
  | 2.6762        | 21.43 | 12000 | 4.7141          | 1.1612 |
  | 2.6833        | 22.32 | 12500 | 4.6789          | 1.0578 |
  | 2.6688        | 23.21 | 13000 | 4.2029          | 1.1971 |
  | 2.6717        | 24.11 | 13500 | 4.3582          | 1.1606 |
  | 2.6414        | 25.0  | 14000 | 4.3469          | 1.2859 |
  | 2.6585        | 25.89 | 14500 | 4.4786          | 1.0517 |
  | 2.6379        | 26.79 | 15000 | 4.1083          | 1.1800 |
  | 2.6453        | 27.68 | 15500 | 4.5773          | 1.0365 |
  | 2.6588        | 28.57 | 16000 | 4.5645          | 1.1381 |
  | 2.6289        | 29.46 | 16500 | 4.4557          | 1.0985 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 1.18.3
  - Tokenizers 0.13.2
  