readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-base-cv-10000
    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-base-cv-10000
  
  This model is a fine-tuned version of [jiobiala24/wav2vec2-base-cv](https://huggingface.co/jiobiala24/wav2vec2-base-cv) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.3393
  - Wer: 0.3684
  
  ## 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
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 0.4243        | 1.6   | 1000  | 0.7742          | 0.4210 |
  | 0.3636        | 3.2   | 2000  | 0.8621          | 0.4229 |
  | 0.2638        | 4.8   | 3000  | 0.9328          | 0.4094 |
  | 0.2273        | 6.4   | 4000  | 0.9556          | 0.4087 |
  | 0.187         | 8.0   | 5000  | 0.9093          | 0.4019 |
  | 0.1593        | 9.6   | 6000  | 0.9842          | 0.4029 |
  | 0.1362        | 11.2  | 7000  | 1.0651          | 0.4077 |
  | 0.1125        | 12.8  | 8000  | 1.0550          | 0.3959 |
  | 0.103         | 14.4  | 9000  | 1.1919          | 0.4002 |
  | 0.0948        | 16.0  | 10000 | 1.1901          | 0.3983 |
  | 0.0791        | 17.6  | 11000 | 1.1091          | 0.3860 |
  | 0.0703        | 19.2  | 12000 | 1.2823          | 0.3904 |
  | 0.0641        | 20.8  | 13000 | 1.2625          | 0.3817 |
  | 0.057         | 22.4  | 14000 | 1.2821          | 0.3776 |
  | 0.0546        | 24.0  | 15000 | 1.2975          | 0.3770 |
  | 0.0457        | 25.6  | 16000 | 1.2998          | 0.3714 |
  | 0.0433        | 27.2  | 17000 | 1.3574          | 0.3721 |
  | 0.0423        | 28.8  | 18000 | 1.3393          | 0.3684 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu111
  - Datasets 1.13.3
  - Tokenizers 0.10.3
  