readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-base-checkpoint-5
    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-checkpoint-5
  
  This model is a fine-tuned version of [jiobiala24/wav2vec2-base-checkpoint-4](https://huggingface.co/jiobiala24/wav2vec2-base-checkpoint-4) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9849
  - Wer: 0.3354
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 0.3947        | 1.96  | 1000  | 0.5749          | 0.3597 |
  | 0.2856        | 3.93  | 2000  | 0.6212          | 0.3479 |
  | 0.221         | 5.89  | 3000  | 0.6280          | 0.3502 |
  | 0.1755        | 7.86  | 4000  | 0.6517          | 0.3526 |
  | 0.1452        | 9.82  | 5000  | 0.7115          | 0.3481 |
  | 0.1256        | 11.79 | 6000  | 0.7687          | 0.3509 |
  | 0.1117        | 13.75 | 7000  | 0.7785          | 0.3490 |
  | 0.0983        | 15.72 | 8000  | 0.8115          | 0.3442 |
  | 0.0877        | 17.68 | 9000  | 0.8290          | 0.3429 |
  | 0.0799        | 19.65 | 10000 | 0.8517          | 0.3412 |
  | 0.0733        | 21.61 | 11000 | 0.9370          | 0.3448 |
  | 0.066         | 23.58 | 12000 | 0.9157          | 0.3410 |
  | 0.0623        | 25.54 | 13000 | 0.9673          | 0.3377 |
  | 0.0583        | 27.5  | 14000 | 0.9804          | 0.3348 |
  | 0.0544        | 29.47 | 15000 | 0.9849          | 0.3354 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu111
  - Datasets 1.13.3
  - Tokenizers 0.10.3
  