readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-base-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-base-2
  
  This model is a fine-tuned version of [jiobiala24/wav2vec2-base-1](https://huggingface.co/jiobiala24/wav2vec2-base-1) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9415
  - Wer: 0.3076
  
  ## 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: 32
  - 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 0.4206        | 1.96  | 1000  | 0.6022          | 0.3435 |
  | 0.3278        | 3.93  | 2000  | 0.6191          | 0.3344 |
  | 0.2604        | 5.89  | 3000  | 0.6170          | 0.3288 |
  | 0.2135        | 7.86  | 4000  | 0.6590          | 0.3239 |
  | 0.1805        | 9.82  | 5000  | 0.7359          | 0.3289 |
  | 0.1582        | 11.79 | 6000  | 0.7450          | 0.3276 |
  | 0.1399        | 13.75 | 7000  | 0.7914          | 0.3218 |
  | 0.1252        | 15.72 | 8000  | 0.8254          | 0.3185 |
  | 0.1095        | 17.68 | 9000  | 0.8524          | 0.3184 |
  | 0.1           | 19.65 | 10000 | 0.8340          | 0.3165 |
  | 0.0905        | 21.61 | 11000 | 0.8846          | 0.3161 |
  | 0.0819        | 23.58 | 12000 | 0.8994          | 0.3142 |
  | 0.0763        | 25.54 | 13000 | 0.9018          | 0.3134 |
  | 0.0726        | 27.5  | 14000 | 0.9552          | 0.3081 |
  | 0.0668        | 29.47 | 15000 | 0.9415          | 0.3076 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu111
  - Datasets 1.13.3
  - Tokenizers 0.10.3
  