readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-demo-M01
    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
  
  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: 2.7099
  - Wer: 1.4021
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 7.3895        | 0.9   | 500   | 2.9817          | 1.0007 |
  | 3.0164        | 1.8   | 1000  | 2.9513          | 1.2954 |
  | 3.0307        | 2.7   | 1500  | 2.8709          | 1.3286 |
  | 3.1314        | 3.6   | 2000  | 2.8754          | 1.0    |
  | 3.0395        | 4.5   | 2500  | 2.9289          | 1.0    |
  | 3.2647        | 5.41  | 3000  | 2.8134          | 1.0014 |
  | 2.9821        | 6.31  | 3500  | 2.8370          | 1.3901 |
  | 2.9262        | 7.21  | 4000  | 2.8731          | 1.3809 |
  | 2.9982        | 8.11  | 4500  | 4.4794          | 1.3958 |
  | 3.0807        | 9.01  | 5000  | 2.8268          | 1.3951 |
  | 2.8873        | 9.91  | 5500  | 2.8014          | 1.5336 |
  | 2.8755        | 10.81 | 6000  | 2.8010          | 1.3873 |
  | 3.2618        | 11.71 | 6500  | 3.1033          | 1.3463 |
  | 3.0063        | 12.61 | 7000  | 2.7906          | 1.3753 |
  | 2.8481        | 13.51 | 7500  | 2.7874          | 1.3837 |
  | 2.876         | 14.41 | 8000  | 2.8239          | 1.0636 |
  | 2.8966        | 15.32 | 8500  | 2.7753          | 1.3915 |
  | 2.8839        | 16.22 | 9000  | 2.7874          | 1.3223 |
  | 2.8351        | 17.12 | 9500  | 2.7755          | 1.3915 |
  | 2.8185        | 18.02 | 10000 | 2.7600          | 1.3908 |
  | 2.8193        | 18.92 | 10500 | 2.7542          | 1.3915 |
  | 2.8023        | 19.82 | 11000 | 2.7528          | 1.3915 |
  | 2.7934        | 20.72 | 11500 | 2.7406          | 1.3915 |
  | 2.8043        | 21.62 | 12000 | 2.7419          | 1.3915 |
  | 2.7941        | 22.52 | 12500 | 2.7407          | 1.3915 |
  | 2.7854        | 23.42 | 13000 | 2.7277          | 1.3915 |
  | 2.7924        | 24.32 | 13500 | 2.7279          | 1.3915 |
  | 2.7644        | 25.23 | 14000 | 2.7217          | 1.3915 |
  | 2.7703        | 26.13 | 14500 | 2.7273          | 1.5032 |
  | 2.7821        | 27.03 | 15000 | 2.7265          | 1.3915 |
  | 2.7632        | 27.93 | 15500 | 2.7154          | 1.3915 |
  | 2.749         | 28.83 | 16000 | 2.7125          | 1.3958 |
  | 2.7515        | 29.73 | 16500 | 2.7099          | 1.4021 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 1.18.3
  - Tokenizers 0.13.2
  