readme: ---
  language:
  - pt
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - generated_from_trainer
  - pt
  - robust-speech-event
  - hf-asr-leaderboard
  model-index:
  - name: wav2vec2-xls-r-1b-portuguese-CORAA-3
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 8
        type: mozilla-foundation/common_voice_8_0
        args: pt
      metrics:
      - name: Test WER
        type: wer
        value: 71.67
      - name: Test CER
        type: cer
        value: 30.64
    - 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: 68.18
      - name: Test CER
        type: cer
        value: 28.34
    - 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: 56.76
      - name: Test CER
        type: cer
        value: 23.7
  ---
  
  <!-- 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-xls-r-1b-portuguese-CORAA-3
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on [CORAA dataset](https://github.com/nilc-nlp/CORAA).
  It achieves the following results on the evaluation set:
  - Loss: 1.0029
  - Wer: 0.6020
  
  ## 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: 0.0003
  - train_batch_size: 4
  - eval_batch_size: 8
  - seed: 42
  - gradient_accumulation_steps: 4
  - 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: 5000
  - training_steps: 30000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 2.0169        | 0.21  | 5000  | 1.9582          | 0.9283 |
  | 1.8561        | 0.42  | 10000 | 1.6144          | 0.8554 |
  | 1.6823        | 0.63  | 15000 | 1.4165          | 0.7710 |
  | 1.52          | 0.84  | 20000 | 1.2441          | 0.7289 |
  | 1.3757        | 1.05  | 25000 | 1.1061          | 0.6491 |
  | 1.2377        | 1.26  | 30000 | 1.0029          | 0.6020 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.3.dev0
  - Tokenizers 0.11.0
  