readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: pseudolabeling-step1-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. -->
  
  # pseudolabeling-step1-F04
  
  This model is a fine-tuned version of [yongjian/wav2vec2-large-a](https://huggingface.co/yongjian/wav2vec2-large-a) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5392
  - Wer: 0.8870
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 21.4261       | 1.71  | 500  | 3.2064          | 1.0    |
  | 2.9275        | 3.42  | 1000 | 2.6461          | 1.2637 |
  | 2.49          | 5.14  | 1500 | 2.0627          | 1.2527 |
  | 1.8582        | 6.85  | 2000 | 1.6367          | 1.1978 |
  | 1.5071        | 8.56  | 2500 | 1.2845          | 1.1743 |
  | 1.2181        | 10.27 | 3000 | 1.1395          | 1.1586 |
  | 1.0386        | 11.99 | 3500 | 1.0155          | 1.0926 |
  | 0.9307        | 13.7  | 4000 | 0.8144          | 1.0628 |
  | 0.8073        | 15.41 | 4500 | 0.7666          | 1.1146 |
  | 0.7209        | 17.12 | 5000 | 0.7020          | 1.0911 |
  | 0.6618        | 18.84 | 5500 | 0.6829          | 1.0612 |
  | 0.6079        | 20.55 | 6000 | 0.6023          | 0.9937 |
  | 0.5242        | 22.26 | 6500 | 0.6057          | 0.9827 |
  | 0.4848        | 23.97 | 7000 | 0.5802          | 0.9435 |
  | 0.4602        | 25.68 | 7500 | 0.5376          | 0.9027 |
  | 0.446         | 27.4  | 8000 | 0.5351          | 0.8964 |
  | 0.4245        | 29.11 | 8500 | 0.5392          | 0.8870 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 1.18.3
  - Tokenizers 0.13.2
  