readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  model-index:
  - name: wav2vec2-demo-M04-2
    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-M04-2
  
  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: 2.0168
  - Wer: 1.2882
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 21.8298       | 0.88  | 500   | 3.2643          | 1.0    |
  | 3.2319        | 1.75  | 1000  | 2.8027          | 1.0    |
  | 2.769         | 2.63  | 1500  | 2.4684          | 1.0    |
  | 2.0823        | 3.5   | 2000  | 1.9137          | 1.6482 |
  | 1.3094        | 4.38  | 2500  | 1.7267          | 1.6094 |
  | 0.9654        | 5.25  | 3000  | 1.7523          | 1.4882 |
  | 0.7505        | 6.13  | 3500  | 1.5588          | 1.5353 |
  | 0.6364        | 7.01  | 4000  | 1.5428          | 1.4706 |
  | 0.5307        | 7.88  | 4500  | 1.6277          | 1.4765 |
  | 0.4664        | 8.76  | 5000  | 1.6817          | 1.3718 |
  | 0.4243        | 9.63  | 5500  | 1.7682          | 1.4541 |
  | 0.3911        | 10.51 | 6000  | 1.8567          | 1.4094 |
  | 0.3555        | 11.38 | 6500  | 1.7248          | 1.3694 |
  | 0.3252        | 12.26 | 7000  | 1.8712          | 1.4012 |
  | 0.3072        | 13.13 | 7500  | 2.0088          | 1.4424 |
  | 0.2956        | 14.01 | 8000  | 1.8649          | 1.3576 |
  | 0.283         | 14.89 | 8500  | 1.8951          | 1.4035 |
  | 0.2682        | 15.76 | 9000  | 1.8762          | 1.3976 |
  | 0.2465        | 16.64 | 9500  | 1.8406          | 1.34   |
  | 0.2344        | 17.51 | 10000 | 1.9975          | 1.3294 |
  | 0.2269        | 18.39 | 10500 | 1.9207          | 1.3176 |
  | 0.2053        | 19.26 | 11000 | 2.0406          | 1.3412 |
  | 0.1934        | 20.14 | 11500 | 1.9039          | 1.2859 |
  | 0.2018        | 21.02 | 12000 | 1.8337          | 1.3212 |
  | 0.169         | 21.89 | 12500 | 1.9120          | 1.3071 |
  | 0.1742        | 22.77 | 13000 | 2.0650          | 1.3153 |
  | 0.1571        | 23.64 | 13500 | 2.0369          | 1.3165 |
  | 0.1403        | 24.52 | 14000 | 2.0420          | 1.2894 |
  | 0.1474        | 25.39 | 14500 | 1.9529          | 1.2847 |
  | 0.1373        | 26.27 | 15000 | 2.0818          | 1.3129 |
  | 0.1222        | 27.15 | 15500 | 1.9551          | 1.2753 |
  | 0.1182        | 28.02 | 16000 | 2.0138          | 1.2659 |
  | 0.1357        | 28.9  | 16500 | 1.9976          | 1.2859 |
  | 0.1158        | 29.77 | 17000 | 2.0168          | 1.2882 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 1.18.3
  - Tokenizers 0.13.2
  