readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-base-checkpoint-6
    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-6
  
  This model is a fine-tuned version of [jiobiala24/wav2vec2-base-checkpoint-5](https://huggingface.co/jiobiala24/wav2vec2-base-checkpoint-5) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9738
  - Wer: 0.3323
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 0.3435        | 1.82  | 1000  | 0.5637          | 0.3419 |
  | 0.2599        | 3.65  | 2000  | 0.5804          | 0.3473 |
  | 0.2043        | 5.47  | 3000  | 0.6481          | 0.3474 |
  | 0.1651        | 7.3   | 4000  | 0.6937          | 0.3452 |
  | 0.1376        | 9.12  | 5000  | 0.7221          | 0.3429 |
  | 0.118         | 10.95 | 6000  | 0.7634          | 0.3441 |
  | 0.105         | 12.77 | 7000  | 0.7789          | 0.3444 |
  | 0.0925        | 14.6  | 8000  | 0.8209          | 0.3444 |
  | 0.0863        | 16.42 | 9000  | 0.8293          | 0.3440 |
  | 0.0756        | 18.25 | 10000 | 0.8553          | 0.3412 |
  | 0.0718        | 20.07 | 11000 | 0.9006          | 0.3430 |
  | 0.0654        | 21.9  | 12000 | 0.9541          | 0.3458 |
  | 0.0605        | 23.72 | 13000 | 0.9400          | 0.3350 |
  | 0.0552        | 25.55 | 14000 | 0.9547          | 0.3363 |
  | 0.0543        | 27.37 | 15000 | 0.9715          | 0.3348 |
  | 0.0493        | 29.2  | 16000 | 0.9738          | 0.3323 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.10.0+cu111
  - Datasets 1.13.3
  - Tokenizers 0.10.3
  