readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-demo-F03
    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-F03
  
  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: 2.8742
  - Wer: 1.2914
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 6.4808        | 0.97  | 500   | 3.0628          | 1.1656 |
  | 2.9947        | 1.94  | 1000  | 3.0334          | 1.1523 |
  | 2.934         | 2.91  | 1500  | 3.0520          | 1.1648 |
  | 2.9317        | 3.88  | 2000  | 3.3808          | 1.0    |
  | 3.0008        | 4.85  | 2500  | 3.0342          | 1.2559 |
  | 3.112         | 5.83  | 3000  | 3.1228          | 1.1258 |
  | 2.8972        | 6.8   | 3500  | 2.9885          | 1.2914 |
  | 2.8911        | 7.77  | 4000  | 3.2586          | 1.2754 |
  | 2.9884        | 8.74  | 4500  | 3.0487          | 1.2090 |
  | 2.873         | 9.71  | 5000  | 2.9382          | 1.2914 |
  | 3.3551        | 10.68 | 5500  | 3.2607          | 1.2844 |
  | 3.6426        | 11.65 | 6000  | 3.0053          | 1.0242 |
  | 2.9184        | 12.62 | 6500  | 2.9219          | 1.2828 |
  | 2.8384        | 13.59 | 7000  | 2.9530          | 1.2816 |
  | 2.8855        | 14.56 | 7500  | 2.9978          | 1.0121 |
  | 2.8479        | 15.53 | 8000  | 2.9722          | 1.0977 |
  | 2.8241        | 16.5  | 8500  | 2.9670          | 1.3082 |
  | 2.807         | 17.48 | 9000  | 2.9841          | 1.2914 |
  | 2.8115        | 18.45 | 9500  | 2.9484          | 1.2977 |
  | 2.8123        | 19.42 | 10000 | 2.9310          | 1.2914 |
  | 3.0291        | 20.39 | 10500 | 2.9665          | 1.2902 |
  | 2.8735        | 21.36 | 11000 | 2.9245          | 1.1160 |
  | 2.8164        | 22.33 | 11500 | 2.9137          | 1.2914 |
  | 2.8084        | 23.3  | 12000 | 2.9543          | 1.1891 |
  | 2.8079        | 24.27 | 12500 | 2.9179          | 1.4516 |
  | 2.7916        | 25.24 | 13000 | 2.8971          | 1.2926 |
  | 2.7824        | 26.21 | 13500 | 2.8990          | 1.2914 |
  | 2.7555        | 27.18 | 14000 | 2.9004          | 1.2914 |
  | 2.7803        | 28.16 | 14500 | 2.8747          | 1.2910 |
  | 2.753         | 29.13 | 15000 | 2.8742          | 1.2914 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 1.18.3
  - Tokenizers 0.13.2
  