readme: ---
  language:
  - pt
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - generated_from_trainer
  - hf-asr-leaderboard
  - mozilla-foundation/common_voice_7_0
  - pt
  - robust-speech-event
  datasets:
  - mozilla-foundation/common_voice_7_0
  model-index:
  - name: wav2vec2_base_10k_8khz_pt_cv7_2
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7
        type: mozilla-foundation/common_voice_7_0
        args: pt
      metrics:
      - name: Test WER
        type: wer
        value: 36.9
      - name: Test CER
        type: cer
        value: 14.82
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: sv
      metrics:
      - name: Test WER
        type: wer
        value: 40.53
      - name: Test CER
        type: cer
        value: 16.95
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: pt
      metrics:
      - name: Test WER
        type: wer
        value: 37.15
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: pt
      metrics:
      - name: Test WER
        type: wer
        value: 38.95
  ---
  
  <!-- 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_10k_8khz_pt_cv7_2
  
  This model is a fine-tuned version of [lgris/seasr_2022_base_10k_8khz_pt](https://huggingface.co/lgris/seasr_2022_base_10k_8khz_pt) on the common_voice dataset.
  It achieves the following results on the evaluation set:
  - Loss: 76.3426
  - Wer: 0.1979
  
  ## 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: 1e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 100
  - training_steps: 10000
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 189.1362      | 0.65  | 500   | 80.6347         | 0.2139 |
  | 174.2587      | 1.3   | 1000  | 80.2062         | 0.2116 |
  | 164.676       | 1.95  | 1500  | 78.2161         | 0.2073 |
  | 176.5856      | 2.6   | 2000  | 78.8920         | 0.2074 |
  | 164.3583      | 3.25  | 2500  | 77.2865         | 0.2066 |
  | 161.414       | 3.9   | 3000  | 77.8888         | 0.2048 |
  | 158.283       | 4.55  | 3500  | 77.3472         | 0.2033 |
  | 159.2265      | 5.19  | 4000  | 79.0953         | 0.2036 |
  | 156.3967      | 5.84  | 4500  | 76.6855         | 0.2029 |
  | 154.2743      | 6.49  | 5000  | 77.7785         | 0.2015 |
  | 156.6497      | 7.14  | 5500  | 77.1220         | 0.2033 |
  | 157.3038      | 7.79  | 6000  | 76.2926         | 0.2027 |
  | 162.8151      | 8.44  | 6500  | 76.7602         | 0.2013 |
  | 151.8613      | 9.09  | 7000  | 77.4777         | 0.2011 |
  | 153.0225      | 9.74  | 7500  | 76.5206         | 0.2001 |
  | 157.52        | 10.39 | 8000  | 76.1061         | 0.2006 |
  | 145.0592      | 11.04 | 8500  | 76.7855         | 0.1992 |
  | 150.0066      | 11.69 | 9000  | 76.0058         | 0.1988 |
  | 146.8128      | 12.34 | 9500  | 76.2853         | 0.1987 |
  | 146.9148      | 12.99 | 10000 | 76.3426         | 0.1979 |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.11.0
  