readme: ---
  language:
  - es
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  - common_voice
  - generated_from_trainer
  - es
  - robust-speech-event
  - hf-asr-leaderboard
  datasets:
  - common_voice
  model-index:
  - name: wav2vec2-cls-r-300m-es
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 7
        type: mozilla-foundation/common_voice_7_0
        args: es
      metrics:
      - name: Test WER
        type: wer
        value: 37.37
      - name: Test CER
        type: cer
        value: 7.11
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Dev Data
        type: speech-recognition-community-v2/dev_data
        args: es
      metrics:
      - name: Test WER
        type: wer
        value: 55.69
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Robust Speech Event - Test Data
        type: speech-recognition-community-v2/eval_data
        args: es
      metrics:
      - name: Test WER
        type: wer
        value: 57.28
  ---
  
  <!-- 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-cls-r-300m-es
  
  This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the COMMON_VOICE - ES dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5160
  - Wer: 0.4016
  
  ## 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: 16
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 8.0
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:----:|:---------------:|:------:|
  | 3.1277        | 1.14  | 500  | 2.0259          | 0.9999 |
  | 1.4111        | 2.28  | 1000 | 1.1251          | 0.8894 |
  | 0.8461        | 3.42  | 1500 | 0.8205          | 0.7244 |
  | 0.5042        | 4.57  | 2000 | 0.6116          | 0.5463 |
  | 0.3072        | 5.71  | 2500 | 0.5507          | 0.4506 |
  | 0.2181        | 6.85  | 3000 | 0.5213          | 0.4177 |
  | 0.1608        | 7.99  | 3500 | 0.5161          | 0.4019 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0.dev0
  - Pytorch 1.10.2+cu102
  - Datasets 1.18.2.dev0
  - Tokenizers 0.11.0
  
  #### Evaluation Commands
  1. To evaluate on `mozilla-foundation/common_voice_7_0` with split `test`
  
  ```bash
  python eval.py --model_id samitizerxu/wav2vec2-xls-r-300m-es --dataset mozilla-foundation/common_voice_7_0 --config es --split test
  ```
  
  2. To evaluate on `speech-recognition-community-v2/dev_data`
  
  ```bash
  python eval.py --model_id samitizerxu/wav2vec2-xls-r-300m-es --dataset speech-recognition-community-v2/dev_data --config es --split validation --chunk_length_s 5.0 --stride_length_s 1.0
  ```